Soumya Ghosh

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 59

Top Topics

Amyotrophic Lateral Sclerosis

Disease Progression

Gaussian Process

Top Venues

Publications

Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky
Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. CoRR (2024)
Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri
When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails. CoRR (2024)
Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions. CoRR (2024)
Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
Large Language Model Confidence Estimation via Black-Box Access. CoRR (2024)
Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
Thermometer: Towards Universal Calibration for Large Language Models. CoRR (2024)
Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici
Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR (2024)
Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
Multi-Level Explanations for Generative Language Models. CoRR (2024)
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick
Are you using test log-likelihood correctly? Trans. Mach. Learn. Res. 2024 (2024)
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
Reliable Gradient-free and Likelihood-free Prompt Tuning. CoRR (2023)
Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves. CoRR (2023)
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. AAAI (2023)
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
Reliable Gradient-free and Likelihood-free Prompt Tuning. EACL (Findings) (2023)
Divya Ramamoorthy, Kristen Severson, Soumya Ghosh, Karen Sachs, Emily G. Baxi, Alyssa N. Coyne, Elizabeth Mosmiller, Lindsey Hayes, Aianna Cerezo, Omar Ahmad, Promit Roy, Steven Zeiler, John W. Krakauer, Jonathan Li, Aneesh Donde, Nhan Huynh, Miriam Adam, Brook T. Wassie, Alexander LeNail, Natasha Leanna Patel-Murray, Yogindra Raghav, Velina Kozareva, Stanislav Tsitkov, Tobias Ehrenberger, Julia A. Kaye, Leandro Lima, Stacia K. Wyman, Edward Vertudes, Naufa Amirani, Krishna Raja, Reuben Thomas, Ryan G. Lim, Ricardo Miramontes, Jie Wu, Vineet Vaibhav, Andrea Matlock, Vidya Venkatraman, Ronald Holewenski, Niveda Sundararaman, Rakhi Pandey, Danica-Mae Manalo, Aaron Frank, Loren Ornelas, Lindsey Panther, Emilda Gomez, Erick Galvez, Daniel Pérez, Imara Meepe, Susan Lei, Louis Pinedo, Chunyan Liu, Ruby Moran, Dhruv Sareen, Barry Landin, Carla Agurto, Guillermo A. Cecchi, Raquel Norel, Sara Thrower, Sarah Luppino, Alanna Farrar, Lindsay Pothier, Hong Yu, Ervin Sinani, Prasha Vigneswaran, Alexander V. Sherman, S. Michelle Farr, Berhan Mandefro, Hannah Trost, Maria G. Banuelos, Veronica Garcia, Michael Workman, Richie Ho, Robert Baloh, Jennifer Roggenbuck, Matthew B. Harms, Carolyn Prina, Sarah Heintzman, Stephen Kolb, Jennifer Stocksdale, Keona Wang, Todd Morgan, Daragh Heitzman, Arish Jamil, Jennifer Jockel-Balsarotti, Elizabeth Karanja, Jesse Markway, Molly McCallum, Tim Miller, Ben Joslin, Deniz Alibazoglu, Senda Ajroud-Driss, Jay C. Beavers, Mary Bellard, Elizabeth Bruce, Nicholas J. Maragakis, Merit E. Cudkowicz, James D. Berry, Terri Thompson, Steven Finkbeiner, Leslie M. Thompson, Jennifer E. Van Eyk, Clive N. Svendsen, Jeffrey D. Rothstein, Jonathan D. Glass, Christina N. Fournier, Alexander Sherman, Christian Lunetta, David Walk, Ghazala Hayat, James Wymer, Kelly Gwathmey, Nicholas Olney, Terry Heiman-Patterson, Ximena Arcila-Londono, Kenneth Faulconer, Ervin Sanani, Alex Berger, Julia Mirochnick, Todd M. Herrington, Kenney Ng, Ernest Fraenkel
Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data. Nat. Comput. Sci. 2 (9) (2022)
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick
Are you using test log-likelihood correctly? CoRR (2022)
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)
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 (2022)
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)
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. CoRR (2022)
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)
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)
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 (2021)
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 (2021)
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)
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) (2021)
Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin
Post-hoc loss-calibration for Bayesian neural networks. UAI (2021)
Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin
Post-hoc loss-calibration for Bayesian neural networks. CoRR (2021)
Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals. CoRR (2021)
Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick
Approximate Cross-Validation for Structured Models. CoRR (2020)
Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick
Approximate Cross-Validation for Structured Models. NeurIPS (2020)
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)
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 (2020)
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) (2020)
Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
Model Fusion with Kullback-Leibler Divergence. CoRR (2020)
Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
Model Fusion with Kullback-Leibler Divergence. ICML (2020)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
Bayesian Nonparametric Federated Learning of Neural Networks. ICML (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
Statistical Model Aggregation via Parameter Matching. CoRR (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
Statistical Model Aggregation via Parameter Matching. NeurIPS (2019)
Kristen A. Severson, Soumya Ghosh, Kenney Ng
Unsupervised Learning with Contrastive Latent Variable Models. AAAI (2019)
Jiayu Yao, Weiwei Pan, Soumya Ghosh, Finale Doshi-Velez
Quality of Uncertainty Quantification for Bayesian Neural Network Inference. CoRR (2019)
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
Bayesian Nonparametric Federated Learning of Neural Networks. CoRR (2019)
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 (2019)
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
Model Selection in Bayesian Neural Networks via Horseshoe Priors. J. Mach. Learn. Res. 20 (2019)
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. ICML (2018)
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 (2018)
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. CoRR (2018)
Animesh Hazra, Soumya Ghosh, Sampad Jash
A Review on DNA Based Cryptographic Techniques. Int. J. Netw. Secur. 20 (6) (2018)
Kristen A. Severson, Soumya Ghosh, Kenney Ng
Unsupervised learning with contrastive latent variable models. CoRR (2018)
Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu
Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care. CoRR (2018)
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)
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)
Vibha Anand, Soumya Ghosh, Amit Anand
Is There a Priority Shift in Mental Health Clinical Trials? MedInfo (2017)
Ajjen Joshi, Soumya Ghosh, Margrit Betke, Stan Sclaroff, Hanspeter Pfister
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks. CVPR (2017)
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)
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)
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)
Vibha Anand, Amos Cahan, Soumya Ghosh
Clinical Trials.Gov: A Topical Analyses. CRI (2017)
Soumya Ghosh, Francesco Maria Delle Fave, Jonathan S. Yedidia
Assumed Density Filtering Methods for Learning Bayesian Neural Networks. AAAI (2016)
Samir Karmakar, Sayantani Banerjee, Soumya Ghosh
Graph theoretic interpretation of Bangla traditional grammar. ICON (2016)
Soumya Ghosh, Yu Cheng, Zhaonan Sun
Deep State Space Models for Computational Phenotyping. ICHI (2016)
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)
Soumya Ghosh, Michalis Raptis, Leonid Sigal, Erik B. Sudderth
Nonparametric Clustering with Distance Dependent Hierarchies. UAI (2014)
Soumya Ghosh, Erik B. Sudderth
Nonparametric learning for layered segmentation of natural images. CVPR (2012)
Soumya Ghosh, Erik B. Sudderth, Matthew Loper, Michael J. Black
From Deformations to Parts: Motion-based Segmentation of 3D Objects. NIPS (2012)
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)
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 (2011)
Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei
Spatial distance dependent Chinese restaurant processes for image segmentation. NIPS (2011)
Soumya Ghosh, Jane Mulligan
A segmentation guided label propagation scheme for autonomous navigation. ICRA (2010)
Soumya Ghosh, Tomasz F. Stepinski, Ricardo Vilalta
Automatic Annotation of Planetary Surfaces With Geomorphic Labels. IEEE Trans. Geosci. Remote. Sens. 48 (1-1) (2010)
Steven Bethard, Soumya Ghosh, James H. Martin, Tamara Sumner
Topic model methods for automatically identifying out-of-scope resources. JCDL (2009)
Soumya Ghosh, Joseph J. Pfeiffer III, Jane Mulligan
A general framework for reconciling multiple weak segmentations of an image. WACV (2009)
Soumya Ghosh, Soundararajan Srinivasan, Burton Andrews
Using weak supervision in learning Gaussian mixture models. IJCNN (2009)
Tomasz F. Stepinski, Ricardo Vilalta, Soumya Ghosh
Machine Learning Tools for Automatic Mapping of Martian Landforms. IEEE Intell. Syst. 22 (6) (2007)
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
Machine Learning for Automatic Mapping of Planetary Surfaces. AAAI (2007)
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification. Discovery Science (2006)