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2020 – today
- 2024
[c96]Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash, Sowmya Ramaswamy Krishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri:
Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback. AAAI 2024: 21-29- [c95]Shubham Gandhi
, Manasi Patwardhan, Jyotsana Khatri, Lovekesh Vig, Raveendra Kumar Medicherla:
Translation of Low-Resource COBOL to Logically Correct and Readable Java leveraging High-Resource Java Refinement. LLM4CODE@ICSE 2024: 46-53 - [c94]Muskan Gupta, Priyanka Gupta, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
SCM4SR: Structural Causal Model-based Data Augmentation for Robust Session-based Recommendation. SIGIR 2024: 2609-2613 - [i71]Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Acceleron: A Tool to Accelerate Research Ideation. CoRR abs/2403.04382 (2024) - [i70]Shubham Paliwal, Arushi Jain, Monika Sharma, Vikram Jamwal, Lovekesh Vig:
CustomText: Customized Textual Image Generation using Diffusion Models. CoRR abs/2405.12531 (2024) - [i69]Arushi Jain, Shubham Paliwal, Monika Sharma, Vikram Jamwal, Lovekesh Vig:
Multi-Subject Personalization. CoRR abs/2405.12742 (2024) - [i68]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig, Gautam Shroff:
SmartFlow: Robotic Process Automation using LLMs. CoRR abs/2405.12842 (2024) - [i67]Pushpdeep Singh, Mayur Patidar, Lovekesh Vig:
Translating Across Cultures: LLMs for Intralingual Cultural Adaptation. CoRR abs/2406.14504 (2024) - 2023
- [c93]Mayur Patidar, Prayushi Faldu, Avinash Kumar Singh, Lovekesh Vig, Indrajit Bhattacharya, Mausam:
Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions. ACL (1) 2023: 10341-10357 - [c92]Amit Sangroya, Suparshva Jain, C. Anantaram, Lovekesh Vig:
Conceptual Explanations of ECG Classification using Large Language Models. AIMLSystems 2023: 59:1-59:3 - [c91]Shabbirhussain Bhaisaheb, Shubham Paliwal, Rajaswa Patil, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Program Synthesis for Complex QA on Charts via Probabilistic Grammar Based Filtered Iterative Back-Translation. EACL (Findings) 2023: 2456-2470 - [c90]Jyoti Narwariya, Priyanka Gupta, Garima Gupta, Lovekesh Vig, Gautam Shroff:
X4SR: Post-Hoc Explanations for Session-based Recommendations. eCom@SIGIR 2023 - [c89]Shubham Paliwal, Bhagyashree Gaikwad, Mayur Patidar, Manasi Patwardhan, Lovekesh Vig, Meghna Mahajan, Bagya Lakshmi V, Shirish S. Karande:
Ontology Guided Supervised Contrastive Learning For Fine-grained Attribute Extraction From Fashion Images. eCom@SIGIR 2023 - [c88]Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan:
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. EMBC 2023: 1-4 - [c87]Shubham Paliwal, Manasi Patwardhan, Lovekesh Vig:
Generalization of Fine Granular Extractions from Charts. ICDAR (2) 2023: 94-110 - [c86]Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan:
IKD+: Reliable Low Complexity Deep Models for Retinopathy Classification. ICIP 2023: 2400-2404 - [c85]Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig:
Can LLMs solve generative visual analogies? IARML@IJCAI 2023: 30-32 - [c84]Jyotsana Khatri, Vivek Srivastava, Lovekesh Vig:
Can You Translate for Me? Code-Switched Machine Translation with Large Language Models. IJCNLP (2) 2023: 83-92 - [c83]Rishabh Patra, Ramya Hebbalaguppe, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. WACV 2023: 1541-1549 - [i66]S. I Harini, Gautam Shroff, Ashwin Srinivasan, Prayushi Faldu, Lovekesh Vig:
Neuro-symbolic Meta Reinforcement Learning for Trading. CoRR abs/2302.08996 (2023) - [i65]Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan:
Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification. CoRR abs/2302.09833 (2023) - [i64]Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan:
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification. CoRR abs/2303.02310 (2023) - [i63]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
Symbolic Regression for PDEs using Pruned Differentiable Programs. CoRR abs/2303.07009 (2023) - [i62]Ankita Sontakke, Kanika Kalra, Manasi Patwardhan, Lovekesh Vig, Raveendra Kumar Medicherla, Ravindra Naik, Shrishti Pradhan:
Knowledge Transfer for Pseudo-code Generation from Low Resource Programming Language. CoRR abs/2303.09062 (2023) - [i61]Ritam Majumdar, Shirish Karande, Lovekesh Vig:
DeepEpiSolver: Unravelling Inverse problems in Covid, HIV, Ebola and Disease Transmission. CoRR abs/2303.14194 (2023) - [i60]Krishnam Hasija, Shrishti Pradhan, Manasi Patwardhan, Raveendra Kumar Medicherla, Lovekesh Vig, Ravindra Naik:
Neuro-symbolic Zero-Shot Code Cloning with Cross-Language Intermediate Representation. CoRR abs/2304.13350 (2023) - [i59]Aseem Arora, Shabbirhussain Bhaisaheb, Harshit Nigam, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff:
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting. CoRR abs/2308.02582 (2023) - [i58]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
HyperLoRA for PDEs. CoRR abs/2308.09290 (2023) - [i57]Ritam Majumdar, Shirish Karande, Lovekesh Vig:
How important are specialized transforms in Neural Operators? CoRR abs/2308.09293 (2023) - [i56]Ritam Majumdar, Amey Varhade, Shirish S. Karande, Lovekesh Vig:
Can Physics Informed Neural Operators Self Improve? CoRR abs/2311.13885 (2023) - 2022
- [c82]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract). AAAI 2022: 13055-13056 - [c81]Manu Sheoran, Monika Sharma, Meghal Dani, Lovekesh Vig:
Handling Domain Shift for Lesion Detection via Semi-supervised Domain Adaptation. ACCV (Workshops) 2022: 102-116 - [c80]Amit Sangroya, Suparshva Jain, Lovekesh Vig, C. Anantaram, Arijit Ukil, Sundeep Khandelwal:
Generating Conceptual Explanations for DL based ECG Classification Model. FLAIRS 2022 - [c79]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
An Efficient Anchor-Free Universal Lesion Detection in Ct-Scans. ISBI 2022: 1-4 - [c78]Vaibhav Varshney, Mayur Patidar, Rajat Kumar, Lovekesh Vig, Gautam Shroff:
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection. NAACL-HLT (Findings) 2022: 1113-1127 - [c77]Rajat Kumar, Mayur Patidar, Vaibhav Varshney, Lovekesh Vig, Gautam Shroff:
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering. NAACL-HLT 2022: 1836-1853 - [c76]Atharv Sonwane, Abhinav Lalwani, Sweta Mahajan, Gautam Shroff, Lovekesh Vig:
Neural Analogical Reasoning. NeSy 2022: 120-141 - [c75]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. NeSy 2022: 142-154 - [c74]Rajaswa Patil, Manasi Patwardhan, Shirish Karande, Lovekesh Vig, Gautam Shroff:
Exploring Dimensions of Generalizability and Few-shot Transfer for Text-to-SQL Semantic Parsing. TL4NLP 2022: 103-114 - [i55]Garima Gupta, Lovekesh Vig, Gautam Shroff:
DRTCI: Learning Disentangled Representations for Temporal Causal Inference. CoRR abs/2201.08137 (2022) - [i54]Jyoti Narwariya, Chetan Verma, Pankaj Malhotra, Lovekesh Vig, Easwar Subramanian, Sanjay Bhat:
Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs. CoRR abs/2202.05517 (2022) - [i53]Diksha Garg, Pankaj Malhotra, Anil Bhatia, Sanjay Bhat, Lovekesh Vig, Gautam Shroff:
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression. CoRR abs/2202.12578 (2022) - [i52]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. CoRR abs/2203.06852 (2022) - [i51]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words. CoRR abs/2203.06873 (2022) - [i50]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection. CoRR abs/2203.06886 (2022) - [i49]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
An Efficient Anchor-free Universal Lesion Detection in CT-scans. CoRR abs/2203.16074 (2022) - [i48]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig:
On NeuroSymbolic Solutions for PDEs. CoRR abs/2207.06240 (2022) - [i47]Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. CoRR abs/2209.08750 (2022) - [i46]Vedant Shah, Aditya Agrawal, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Tanmay T. Verlekar:
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss. CoRR abs/2211.16047 (2022) - [i45]Ramya Hebbalaguppe, Rishabh Patra, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig:
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning. CoRR abs/2212.10005 (2022) - [i44]Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana:
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs. CoRR abs/2212.10032 (2022) - [i43]Mayur Patidar, Avinash Kumar Singh, Prayushi Faldu, Lovekesh Vig, Indrajit Bhattacharya, Mausam:
Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions. CoRR abs/2212.10189 (2022) - 2021
- [j16]Kushal Veer Singh, Ajay Kumar Verma, Lovekesh Vig:
Deep learning based network similarity for model selection. Data Sci. 4(2): 63-83 (2021) - [j15]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig:
Incorporating symbolic domain knowledge into graph neural networks. Mach. Learn. 110(7): 1609-1636 (2021) - [c73]Manu Sheoran, Meghal Dani, Monika Sharma, Lovekesh Vig:
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection. BMVC 2021: 413 - [c72]Priyanka Gupta, Ankit Sharma, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
CauSeR: Causal Session-based Recommendations for Handling Popularity Bias. CIKM 2021: 3048-3052 - [c71]Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words. ESANN 2021 - [c70]Shruti Kunde, Amey Pandit, Kushagra Mahajan, Monika Sharma, Rekha Singhal, Lovekesh Vig:
Data-Efficient Training of High-Resolution Images in Medical Domain. ESANN 2021 - [c69]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. ICDM 2021: 161-170 - [c68]Manasi Malik, Garima Gupta, Lovekesh Vig, Gautam Shroff:
BCQ4DCA: Budget Constrained Deep Q-Network for Dynamic Campaign Allocation in Computational Advertising. IJCNN 2021: 1-8 - [c67]Shubham Paliwal, Monika Sharma, Lovekesh Vig:
OSSR-PID: One-Shot Symbol Recognition in P&ID Sheets using Path Sampling and GCN. IJCNN 2021: 1-8 - [c66]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy:
Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design. ILP 2021: 78-94 - [c65]Shubham Paliwal, Arushi Jain, Monika Sharma, Lovekesh Vig:
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams. PAKDD (Workshops) 2021: 168-180 - [i42]Shubham Paliwal, Arushi Jain, Monika Sharma, Lovekesh Vig:
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams. CoRR abs/2109.03794 (2021) - [i41]Shubham Paliwal, Monika Sharma, Lovekesh Vig:
OSSR-PID: One-Shot Symbol Recognition in P&ID Sheets using Path Sampling and GCN. CoRR abs/2109.03849 (2021) - [i40]Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems. CoRR abs/2110.09947 (2021) - [i39]Mrinal Rawat, Ramya Hebbalaguppe, Lovekesh Vig:
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation. CoRR abs/2111.00506 (2021) - [i38]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning. CoRR abs/2111.10361 (2021) - 2020
- [j14]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis Using Deep Neural Networks. J. Heal. Informatics Res. 4(2): 112-137 (2020) - [j13]Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff:
Constructing generative logical models for optimisation problems using domain knowledge. Mach. Learn. 109(7): 1371-1392 (2020) - [c64]Nikhil Jaiswal, Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal, Lovekesh Vig:
Improving NMT via Filtered Back Translation. WAT@AAC/IJCNLPL 2020: 154-159 - [c63]Amit Sangroya, Mouli Rastogi, C. Anantaram, Lovekesh Vig:
Guided-LIME: Structured Sampling based Hybrid Approach towards Explaining Blackbox Machine Learning Models. CIKM (Workshops) 2020 - [c62]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. COMAD/CODS 2020: 28-36 - [c61]Nikita Goel, Monika Sharma, Lovekesh Vig:
Font-ProtoNet: Prototypical Network based Font Identification of Document Images in Low Data Regime. CVPR Workshops 2020: 2369-2376 - [c60]Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan:
Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. CVPR Workshops 2020: 2377-2385 - [c59]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Meta-DermDiagnosis: Few-Shot Skin Disease Identification using Meta-Learning. CVPR Workshops 2020: 3142-3151 - [c58]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. ESANN 2020: 25-30 - [c57]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Causal Attention Model for Multi-touch Attribution. ICDM (Workshops) 2020: 79-86 - [c56]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Vidya Vikas:
Capsule Based Neural Network Architecture to perform completeness check for Patent Eligibility Process. IJCNN 2020: 1-8 - [c55]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CD@KDD 2020: 39-61 - [c54]Himani Srivastava, Prerna Khurana, Saurabh Srivastava, Vaibhav Varshney, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Improved Question Answering using Domain Prediction. Converse@KDD 2020 - [c53]Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff:
CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. TIA@MICCAI 2020: 61-73 - [c52]Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan:
A Case Study of Transfer of Lesion-Knowledge. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 138-145 - [i37]Shubham Paliwal, Vishwanath D, Rohit Rahul, Monika Sharma, Lovekesh Vig:
TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images. CoRR abs/2001.01469 (2020) - [i36]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. CoRR abs/2004.13446 (2020) - [i35]Jyoti Narwariya, Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Gautam Shroff:
Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation. CoRR abs/2006.16556 (2020) - [i34]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Handling Variable-Dimensional Time Series with Graph Neural Networks. CoRR abs/2007.00411 (2020) - [i33]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
Hi-CI: Deep Causal Inference in High Dimensions. CoRR abs/2008.09858 (2020) - [i32]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig:
Incorporating Symbolic Domain Knowledge into Graph Neural Networks. CoRR abs/2010.13900 (2020) - [i31]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs/2012.08984 (2020) - [i30]Rishab Khincha, Soundarya Krishnan, Krishnan Guru-Murthy, Tirtharaj Dash, Lovekesh Vig, Ashwin Srinivasan:
Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays. CoRR abs/2012.10787 (2020) - [i29]Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Casual Attention Model for Multi-touch Attribution. CoRR abs/2012.11403 (2020)
2010 – 2019
- 2019
- [j12]Sucheta Chauhan, Lovekesh Vig, Shandar Ahmad:
ECG anomaly class identification using LSTM and error profile modeling. Comput. Biol. Medicine 109: 14-21 (2019) - [j11]Sucheta Chauhan, Lovekesh Vig, Michele De Filippo De Grazia, Maurizio Corbetta, Shandar Ahmad, Marco Zorzi:
A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images. Frontiers Neuroinformatics 13: 53 (2019) - [j10]Ashwin Srinivasan, Lovekesh Vig, Michael Bain:
Logical Explanations for Deep Relational Machines Using Relevance Information. J. Mach. Learn. Res. 20: 130:1-130:47 (2019) - [c51]Kaushal Paneri, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters. AAAI 2019: 10003-10004 - [c50]Mayur Patidar, Surabhi Kumari, Manasi Patwardhan, Shirish Karande, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
From Monolingual to Multilingual FAQ Assistant using Multilingual Co-training. DeepLo@EMNLP-IJCNLP 2019: 115-123 - [c49]Arijit Ukil, Pankaj Malhotra, Soma Bandyopadhyay, Tulika Bose, Ishan Sahu, Ayan Mukherjee, Lovekesh Vig, Arpan Pal, Gautam Shroff:
Fusing Features based on Signal Properties and TimeNet for Time Series Classification. ESANN 2019 - [c48]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Character Keypoint-Based Homography Estimation in Scanned Documents for Efficient Information Extraction. CBDAR@ICDAR 2019: 25-30 - [c47]Shubham Singh Paliwal, Vishwanath D, Rohit Rahul, Monika Sharma, Lovekesh Vig:
TableNet: Deep Learning Model for End-to-end Table Detection and Tabular Data Extraction from Scanned Document Images. ICDAR 2019: 128-133 - [c46]Rohit Rahul, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
Automatic Information Extraction from Piping and Instrumentation Diagrams. ICPRAM 2019: 163-172 - [c45]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. IJCNN 2019: 1-8 - [c44]Monika Sharma, Shikha Gupta, Arindam Chowdhury, Lovekesh Vig:
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks. IJCNN 2019: 1-7 - [c43]Saurabh Srivastava, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Hierarchical Capsule Based Neural Network Architecture for Sequence Labeling. IJCNN 2019: 1-8 - [c42]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. NeSy@IJCAI 2019 - [c41]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-Box Optimization. ECML/PKDD (2) 2019: 366-381 - [c40]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Sequence and Time Aware Neighborhood for Session-based Recommendations: STAN. SIGIR 2019: 1069-1072 - [i28]Monika Sharma, Abhishek Verma, Lovekesh Vig:
Learning to Clean: A GAN Perspective. CoRR abs/1901.11382 (2019) - [i27]Rohit Rahul, Shubham Paliwal, Monika Sharma, Lovekesh Vig:
Automatic Information Extraction from Piping and Instrumentation Diagrams. CoRR abs/1901.11383 (2019) - [i26]Vishnu TV, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models. CoRR abs/1903.09795 (2019) - [i25]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks. CoRR abs/1904.00655 (2019) - [i24]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. CoRR abs/1904.12546 (2019) - [i23]Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul:
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. CoRR abs/1906.02427 (2019) - [i22]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-box Optimization. CoRR abs/1907.06901 (2019) - [i21]Priyanka Gupta, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs/1909.04276 (2019) - [i20]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. CoRR abs/1909.07155 (2019) - [i19]Kushagra Mahajan, Monika Sharma, Lovekesh Vig:
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction. CoRR abs/1911.05870 (2019) - [i18]Monika Sharma, Shikha Gupta, Arindam Chowdhury, Lovekesh Vig:
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks. CoRR abs/1911.09375 (2019) - [i17]Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population. CoRR abs/1912.03960 (2019) - 2018
- [c39]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. AAAI Workshops 2018: 699-705 - [c38]Rohit Rahul, Arindam Chowdhury, Animesh, Samarth Mittal, Lovekesh Vig:
Reading Industrial Inspection Sheets by Inferring Visual Relations. ACCV Workshops 2018: 159-173 - [c37]Monika Sharma, Abhishek Verma, Lovekesh Vig:
Learning to Clean: A GAN Perspective. ACCV Workshops 2018: 174-185 - [c36]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. ACCV Workshops 2018: 186-201 - [c35]Arindam Chowdhury, Lovekesh Vig:
An Efficient End-to-End Neural Model for Handwritten Text Recognition. BMVC 2018: 202 - [c34]Mayur Patidar, Puneet Agarwal, Lovekesh Vig, Gautam Shroff:
Automatic Conversational Helpdesk Solution using Seq2Seq and Slot-filling Models. CIKM 2018: 1967-1975 - [c33]Sakti Saurav, Pankaj Malhotra, Vishnu TV, Narendhar Gugulothu, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Online anomaly detection with concept drift adaptation using recurrent neural networks. COMAD/CODS 2018: 78-87 - [c32]Gaurav Garg, Srinidhi Hegde, Ramakrishna Perla, Varun Jain, Lovekesh Vig, Ramya Hebbalaguppe:
DrawInAir: A Lightweight Gestural Interface Based on Fingertip Regression. ECCV Workshops (6) 2018: 229-240 - [c31]Swati, Monika Sharma, Lovekesh Vig:
Automatic Classification of Low-Resolution Chromosomal Images. ECCV Workshops (6) 2018: 315-325 - [c30]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. ESANN 2018 - [c29]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Using Features From Pre-trained TimeNET For Clinical Predictions. KDH@IJCAI 2018: 38-44 - [c28]Monika Sharma, Swati, Lovekesh Vig:
Automatic Chromosome Classification using Deep Attention Based Sequence Learning of Chromosome Bands. IJCNN 2018: 1-8 - [c27]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King:
Large-Scale Assessment of Deep Relational Machines. ILP 2018: 22-37 - [c26]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig:
Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN. KDD 2018: 433-442 - [i16]Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Evolutionary RL for Container Loading. CoRR abs/1805.06664 (2018) - [i15]Ashwin Srinivasan, Lovekesh Vig, Michael Bain:
Logical Explanations for Deep Relational Machines Using Relevance Information. CoRR abs/1807.00595 (2018) - [i14]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks. CoRR abs/1807.01705 (2018) - [i13]Arindam Chowdhury, Lovekesh Vig:
An Efficient End-to-End Neural Model for Handwritten Text Recognition. CoRR abs/1807.07965 (2018) - [i12]Vishal Sunder, Lovekesh Vig, Arnab Chatterjee, Gautam Shroff:
Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learning. CoRR abs/1809.07066 (2018) - [i11]Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan:
Deep Reader: Information extraction from Document images via relation extraction and Natural Language. CoRR abs/1812.04377 (2018) - [i10]Rohit Rahul, Arindam Chowdhury, Animesh, Samarth Mittal, Lovekesh Vig:
Reading Industrial Inspection Sheets by Inferring Visual Relations. CoRR abs/1812.07104 (2018) - [i9]Vishwanath D, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling. CoRR abs/1812.11158 (2018) - 2017
- [j9]Kushal Veer Singh, Lovekesh Vig:
Improved prediction of missing protein interactome links via anomaly detection. Appl. Netw. Sci. 2: 2 (2017) - [c25]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Hybrid BiLSTM-Siamese network for FAQ Assistance. CIKM 2017: 537-545 - [c24]Monika Sharma, Oindrila Saha, Anand Sriraman, Ramya Hebbalaguppe, Lovekesh Vig, Shirish Karande:
Crowdsourcing for Chromosome Segmentation and Deep Classification. CVPR Workshops 2017: 786-793 - [c23]Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension. EACL (1) 2017: 850-859 - [c22]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. ESANN 2017 - [c21]Swati, Gaurav Gupta, Mohit Yadav, Monika Sharma, Lovekesh Vig:
Siamese Networks for Chromosome Classification. ICCV Workshops 2017: 72-81 - [c20]Somdyuti Paul, Lovekesh Vig:
Deterministic Policy Gradient Based Robotic Path Planning with Continuous Action Spaces. ICCV Workshops 2017: 725-733 - [c19]Gaurav Gupta, Swati, Monika Sharma, Lovekesh Vig:
Information Extraction from Hand-Marked Industrial Inspection Sheets. CBDAR@ICDAR 2017: 33-38 - [c18]Sunder Vishal, Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Information Bottleneck Inspired Method For Chat Text Segmentation. IJCNLP(1) 2017: 194-203 - [c17]Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma:
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. ILP 2017: 169-183 - [c16]Monika Sharma, Ramya Hebbalaguppe, Lovekesh Vig:
Pre-trained classifiers with One Shot Similarity for context aware face verification and identification. ISBA 2017: 1-7 - [i8]Karamjit Singh, Garima Gupta, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Deep Convolutional Neural Networks for Pairwise Causality. CoRR abs/1701.00597 (2017) - [i7]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. CoRR abs/1706.08838 (2017) - [i6]Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks. CoRR abs/1709.01073 (2017) - 2016
- [c15]Ankit Verma, Monika Sharma, Ramya Hebbalaguppe, Ehtesham Hassan, Lovekesh Vig:
Automatic Container Code Recognition via Spatial Transformer Networks and Connected Component Region Proposals. ICMLA 2016: 728-733 - [c14]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. ILP 2016: 120-131 - [c13]Ramakrishna Perla, Ehtesham Hassan, Ramya Hebbalaguppe, Monika Sharma, Gaurav Gupta, Lovekesh Vig, Geetika Sharma, Gautam Shroff:
An AR Inspection Framework: Feasibility Study with Multiple AR Devices. ISMAR Adjunct 2016: 221-226 - [c12]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. CoCo@NIPS 2016 - [i5]Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K. Sriram, Gautam Shroff:
ODE - Augmented Training Improves Anomaly Detection in Sensor Data from Machines. CoRR abs/1605.01534 (2016) - [i4]Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection. CoRR abs/1607.00148 (2016) - [i3]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia, Puneet Agarwal:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. CoRR abs/1608.01093 (2016) - [i2]Pankaj Malhotra, Vishnu TV, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder. CoRR abs/1608.06154 (2016) - [i1]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. CoRR abs/1612.06528 (2016) - 2015
- [j8]Manoj Agarwal, Nitin Agrawal, Shikhar Sharma, Lovekesh Vig, Naveen Kumar:
Parallel multi-objective multi-robot coalition formation. Expert Syst. Appl. 42(21): 7797-7811 (2015) - [c11]Sucheta Chauhan, Lovekesh Vig:
Anomaly detection in ECG time signals via deep long short-term memory networks. DSAA 2015: 1-7 - [c10]Urminder Singh, Sucheta Chauhan, A. Krishnamachari, Lovekesh Vig:
Ensemble of deep long short term memory networks for labelling origin of replication sequences. DSAA 2015: 1-7 - [c9]Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Long Short Term Memory Networks for Anomaly Detection in Time Series. ESANN 2015 - [c8]Ankit Verma, Ramya Hebbalaguppe, Lovekesh Vig, Swagat Kumar, Ehtesham Hassan:
Pedestrian Detection via Mixture of CNN Experts and Thresholded Aggregated Channel Features. ICCV Workshops 2015: 555-563 - 2014
- [j7]Manoj Agarwal, Naveen Kumar, Lovekesh Vig:
Non-additive multi-objective robot coalition formation. Expert Syst. Appl. 41(8): 3736-3747 (2014) - 2011
- [j6]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A dual association model for the extinction of animal conditioning. Neurocomputing 74(17): 3531-3542 (2011) - [j5]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
A Neurocomputational Model for the Relation Between Hunger, Dopamine and Action Rate. J. Intell. Syst. 20(4): 373-393 (2011) - [j4]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
Multiple Objective Robot Coalition Formation. J. Intell. Syst. 20(4): 395-413 (2011) - [j3]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A Cognitive Model for Generalization during Sequential Learning. J. Robotics 2011: 617613:1-617613:12 (2011) - [c7]Ashish Gupta, Lovekesh Vig:
A Dual Association Model for Acquisition and Extinction. AI*IA 2011: 139-150 - [c6]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
Multi-objective Robot Coalition Formation for Non-additive Environments. ICIRA (1) 2011: 346-355 - [c5]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
MORCFA: A Multiple Objective Robot Coalition Formation Algorithm. IICAI 2011: 268-279 - [c4]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
On the relation between hunger, dopamine and action rate. IICAI 2011: 1601-1617
2000 – 2009
- 2009
- [c3]Lovekesh Vig, Julie A. Adams:
The Effect of Coalition Imbalance on Multi-Robot Teams. IICAI 2009: 603-615 - 2007
- [j2]Lovekesh Vig, Julie A. Adams:
Coalition Formation: From Software Agents to Robots. J. Intell. Robotic Syst. 50(1): 85-118 (2007) - 2006
- [j1]Lovekesh Vig, Julie A. Adams:
Multi-robot coalition formation. IEEE Trans. Robotics 22(4): 637-649 (2006) - [c2]Lovekesh Vig, Julie A. Adams:
Market-Based Multi-robot Coalition Formation. DARS 2006: 227-236 - 2005
- [c1]Lovekesh Vig, Julie A. Adams:
A Framework for Multi-Robot Coalition Formation. IICAI 2005: 347-363
Coauthor Index
Shubham Paliwal
aka: Shubham Singh Paliwal
aka: Shubham Singh Paliwal
[c94] [i71] [i68] [c91] [c90] [c85] [c83] [i66] [i59] [c82] [c78] [c77] [c76] [c75] [c74] [i55] [i53] [i52] [i47] [i46] [i45] [c72] [c69] [c68] [i40] [i38] [j14] [j13] [c62] [c60] [c58] [c57] [c56] [c55] [c54] [c53] [i36] [i35] [i34] [i33] [i31] [i29] [c51] [c50] [c49] [c45] [c43] [c42] [c41] [c40] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i17] [c39] [c36] [c34] [c33] [c30] [c29] [c26] [i16] [i14] [i12] [i11] [i9] [c25] [c23] [c22] [c18] [i8] [i7] [i6] [c14] [c13] [c12] [i5] [i4] [i3] [i2] [i1] [c9]
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