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2020 – today
- 2023
[c37]Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell:
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. AAAI 2023: 9772-9781- [c36]Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell:
Reliable Gradient-free and Likelihood-free Prompt Tuning. EACL (Findings) 2023: 2371-2384 - [i21]Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell:
Reliable Gradient-free and Likelihood-free Prompt Tuning. CoRR abs/2305.00593 (2023) - [i20]Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri:
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves. CoRR abs/2310.03158 (2023) - 2022
- [c35]William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick:
Measuring the robustness of Gaussian processes to kernel choice. AISTATS 2022: 3308-3331 - [c34]Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang:
Uncertainty Quantification 360: A Hands-on Tutorial. COMAD/CODS 2022: 333-335 - [c33]Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney:
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. NeurIPS 2022 - [c32]Talib A. Al-Sharify, Zinah A. Alshrefy, Hussein Ali Hussein, Zainab T. Al-Sharify, Helen Onyeaka, Mushtaq T. Al-Sharify, Soumya Ghosh:
IoT and E-Learning with the Impact of COVID-19 Pandemic Lockdown on the Undergraduate University Student Blood Pressure Levels. TTSIIT 2022: 73-86 - [i19]Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick
:
Are you using test log-likelihood correctly? CoRR abs/2212.00219 (2022) - [i18]Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney:
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. CoRR abs/2212.06803 (2022) - [i17]Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell:
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. CoRR abs/2212.07359 (2022) - 2021
- [j7]Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng:
DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways. IEEE Trans. Vis. Comput. Graph. 27(9): 3685-3700 (2021) - [c31]Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Cao Xiao, Jimeng Sun:
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders. MLHC 2021: 260-282 - [c30]Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin:
Post-hoc loss-calibration for Bayesian neural networks. UAI 2021: 1403-1412 - [i16]Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri:
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals. CoRR abs/2106.00858 (2021) - [i15]Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang:
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI. CoRR abs/2106.01410 (2021) - [i14]William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick:
Measuring the sensitivity of Gaussian processes to kernel choice. CoRR abs/2106.06510 (2021) - [i13]Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin:
Post-hoc loss-calibration for Bayesian neural networks. CoRR abs/2106.06997 (2021) - 2020
- [j6]Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu:
Complication Risk Profiling in Diabetes Care: A Bayesian Multi-Task and Feature Relationship Learning Approach. IEEE Trans. Knowl. Data Eng. 32(7): 1276-1289 (2020) - [c29]Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon:
Model Fusion with Kullback-Leibler Divergence. ICML 2020: 2038-2047 - [c28]Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh:
Personalized Input-Output Hidden Markov Models for Disease Progression Modeling. MLHC 2020: 309-330 - [c27]Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick:
Approximate Cross-Validation for Structured Models. NeurIPS 2020 - [i12]Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick:
Approximate Cross-Validation for Structured Models. CoRR abs/2006.12669 (2020) - [i11]Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon:
Model Fusion with Kullback-Leibler Divergence. CoRR abs/2007.06168 (2020) - [i10]Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Jimeng Sun:
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders. CoRR abs/2012.10020 (2020)
2010 – 2019
- 2019
- [j5]Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez:
Model Selection in Bayesian Neural Networks via Horseshoe Priors. J. Mach. Learn. Res. 20: 182:1-182:46 (2019) - [c26]Kristen A. Severson, Soumya Ghosh, Kenney Ng:
Unsupervised Learning with Contrastive Latent Variable Models. AAAI 2019: 4862-4869 - [c25]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. ICML 2019: 7252-7261 - [c24]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. NeurIPS 2019: 10954-10964 - [i9]Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng:
DPVis: Visual Exploration of Disease Progression Pathways. CoRR abs/1904.11652 (2019) - [i8]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. CoRR abs/1905.12022 (2019) - [i7]Jiayu Yao, Weiwei Pan, Soumya Ghosh, Finale Doshi-Velez:
Quality of Uncertainty Quantification for Bayesian Neural Network Inference. CoRR abs/1906.09686 (2019) - [i6]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. CoRR abs/1911.00218 (2019) - 2018
- [j4]Animesh Hazra, Soumya Ghosh, Sampad Jash:
A Review on DNA Based Cryptographic Techniques. Int. J. Netw. Secur. 20(6): 1093-1104 (2018) - [c23]Bin Liu, Ying Li, Zhaonan Sun, Soumya Ghosh, Kenney Ng:
Early Prediction of Diabetes Complications from Electronic Health Records: A Multi-Task Survival Analysis Approach. AAAI 2018: 101-108 - [c22]Ajjen Joshi, Soumya Ghosh, Sarah Gunnery, Linda Tickle-Degnen, Stan Sclaroff, Margrit Betke:
Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks. FG 2018: 278-285 - [c21]Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez:
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. ICML 2018: 1739-1748 - [i5]Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu:
Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care. CoRR abs/1802.06476 (2018) - [i4]Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez:
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. CoRR abs/1806.05975 (2018) - [i3]Kristen A. Severson, Soumya Ghosh, Kenney Ng:
Unsupervised learning with contrastive latent variable models. CoRR abs/1811.06094 (2018) - [i2]Melanie F. Pradier, Weiwei Pan, Jiayu Yao, Soumya Ghosh, Finale Doshi-Velez:
Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights. CoRR abs/1811.07006 (2018) - 2017
- [c20]Zhaonan Sun, Ying Li, Soumya Ghosh, Yu Cheng, Amrita Mohan, Cristina Sampaio:
A Data-Driven Method for Generating Robust Symptom Onset Indicators in Disease Registry Data. AMIA 2017 - [c19]Vibha Anand, Amos Cahan, Soumya Ghosh:
Clinical Trials.Gov: A Topical Analyses. CRI 2017 - [c18]Soumya Ghosh, Zhaonan Sun, Ying Li, Yu Cheng, Amrita Mohan, Cristina Sampaio, Jianying Hu:
An Exploration of Latent Structure in Observational Huntington's Disease Studies. CRI 2017 - [c17]Zhaonan Sun, Ying Li, Soumya Ghosh, Yu Cheng, Amrita Mohan, Cristina Sampaio, Jianying Hu:
Exploring Factors that Associated with Missing Values in Observational Huntington's Disease Study Data. CRI 2017 - [c16]Ajjen Joshi, Soumya Ghosh, Margrit Betke, Stan Sclaroff, Hanspeter Pfister:
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks. CVPR 2017: 455-464 - [c15]Vibha Anand, Soumya Ghosh, Amit Anand:
Is There a Priority Shift in Mental Health Clinical Trials? MedInfo 2017: 280-284 - 2016
- [c14]Soumya Ghosh, Francesco Maria Delle Fave, Jonathan S. Yedidia:
Assumed Density Filtering Methods for Learning Bayesian Neural Networks. AAAI 2016: 1589-1595 - [c13]Soumya Ghosh, Yu Cheng, Zhaonan Sun:
Deep State Space Models for Computational Phenotyping. ICHI 2016: 399-402 - [c12]Samir Karmakar, Sayantani Banerjee, Soumya Ghosh:
Graph theoretic interpretation of Bangla traditional grammar. ICON 2016: 129-136 - 2015
- [b1]Soumya Ghosh:
Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects. Brown University, USA, 2015 - 2014
- [c11]Robert L. Hollingshead, David Putrino, Soumya Ghosh, Tele Tan:
Investigation into machine learning algorithms as applied to motor cortex signals for classification of movement stages. EMBC 2014: 1290-1293 - [c10]Soumya Ghosh, Michalis Raptis, Leonid Sigal, Erik B. Sudderth:
Nonparametric Clustering with Distance Dependent Hierarchies. UAI 2014: 260-269 - 2012
- [c9]Soumya Ghosh, Erik B. Sudderth:
Nonparametric learning for layered segmentation of natural images. CVPR 2012: 2272-2279 - [c8]Soumya Ghosh, Erik B. Sudderth, Matthew Loper, Michael J. Black:
From Deformations to Parts: Motion-based Segmentation of 3D Objects. NIPS 2012: 2006-2014 - 2011
- [j3]Sanggyun Kim, David Putrino, Soumya Ghosh, Emery N. Brown:
A Granger Causality Measure for Point Process Models of Ensemble Neural Spiking Activity. PLoS Comput. Biol. 7(3) (2011) - [c7]Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei:
Spatial distance dependent Chinese restaurant processes for image segmentation. NIPS 2011: 1476-1484 - [i1]Debajyoti Mukhopadhyay, Sajal Mukherjee, Soumya Ghosh, Saheli Kar, Young-Chon Kim:
Architecture of A Scalable Dynamic Parallel WebCrawler with High Speed Downloadable Capability for a Web Search Engine. CoRR abs/1102.0676 (2011) - 2010
- [j2]Soumya Ghosh, Tomasz F. Stepinski, Ricardo Vilalta:
Automatic Annotation of Planetary Surfaces With Geomorphic Labels. IEEE Trans. Geosci. Remote. Sens. 48(1-1): 175-185 (2010) - [c6]Soumya Ghosh, Jane Mulligan:
A segmentation guided label propagation scheme for autonomous navigation. ICRA 2010: 895-902
2000 – 2009
- 2009
- [c5]Soumya Ghosh, Soundararajan Srinivasan, Burton Andrews:
Using weak supervision in learning Gaussian mixture models. IJCNN 2009: 973-979 - [c4]Steven Bethard, Soumya Ghosh, James H. Martin, Tamara Sumner:
Topic model methods for automatically identifying out-of-scope resources. JCDL 2009: 19-28 - [c3]Soumya Ghosh, Joseph J. Pfeiffer III, Jane Mulligan:
A general framework for reconciling multiple weak segmentations of an image. WACV 2009: 1-8 - 2007
- [j1]Tomasz F. Stepinski, Ricardo Vilalta, Soumya Ghosh:
Machine Learning Tools for Automatic Mapping of Martian Landforms. IEEE Intell. Syst. 22(6): 100-106 (2007) - [c2]Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta:
Machine Learning for Automatic Mapping of Planetary Surfaces. AAAI 2007: 1807-1812 - 2006
- [c1]Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta:
Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification. Discovery Science 2006: 255-266
Coauthor Index
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last updated on 2023-11-14 01:58 CET by the dblp team
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