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ORCIDLovekesh Vig
- > Home > Persons > Lovekesh Vig
Publications
- 2024
[c93]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- 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 - [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 - [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 - [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) - 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 - [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 - [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) - [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) - 2021
- [j15]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig:
Incorporating symbolic domain knowledge into graph neural networks. Mach. Learn. 110(7): 1609-1636 (2021) - [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 - [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) - [i38]Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash:
Solving Visual Analogies Using Neural Algorithmic Reasoning. CoRR abs/2111.10361 (2021) - 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 - [i32]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig:
Incorporating Symbolic Domain Knowledge into Graph Neural Networks. CoRR abs/2010.13900 (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) - 2018
- [c27]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King:
Large-Scale Assessment of Deep Relational Machines. ILP 2018: 22-37
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last updated on 2024-04-14 03:47 CEST by the dblp team
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