Soumya Ghosh - RankMe

84 papers A* 17A 4B 3Misc 1Journal 42Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	STRAND: Sequence-Conditioned Transport for Single-Cell Perturbations. CoRR Boyang Fu, George Dasoulas, Sameer Gabbita, Xiang Li, Shanghua Gao, Xiao-Rui Su, Soumya Ghosh, Marinka Zitnik
2025	J	`jnl`	Large Language Model Confidence Estimation via Black-Box Access. Trans. Mach. Learn. Res. Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2025	—	`conf`	Multi-Level Explanations for Generative Language Models. ACL (1) 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
2025	J	`jnl`	TEDDY: A Family Of Foundation Models For Understanding Single Cell Biology. CoRR Alexis Chevalier, Soumya Ghosh, Urvi Awasthi, James Watkins, Julia Bieniewska, Nichita Mitrea, Olga Kotova, Kirill Shkura, Andrew Noble, Michael Steinbaugh, Julien Delile, Christoph Meier, Leonid Zhukov, Iya Khalil, Srayanta Mukherjee, Judith Mueller
2024	J	`jnl`	A hybrid DNA cryptography-based encryption algorithm using the fusion of symmetric key techniques. Int. J. Adv. Intell. Paradigms Animesh Hazra, Soumya Ghosh, Sampad Jash
2024	A*	`conf`	Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? NeurIPS Maohao Shen, Jongha Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
2024	J	`jnl`	Are you using test log-likelihood correctly? Trans. Mach. Learn. Res. Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick
2024	J	`jnl`	Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR 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
2024	J	`jnl`	Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods. CoRR Dennis Wei, Inkit Padhi, Soumya Ghosh, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Maria Chang
2024	J	`jnl`	Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions. CoRR Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
2024	J	`jnl`	Large Language Model Confidence Estimation via Black-Box Access. CoRR Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2024	J	`jnl`	Multi-Level Explanations for Generative Language Models. CoRR 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
2024	A*	`conf`	Thermometer: Towards Universal Calibration for Large Language Models. ICML Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2024	J	`jnl`	Thermometer: Towards Universal Calibration for Large Language Models. CoRR Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2024	A*	`conf`	Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. NeurIPS Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky
2024	J	`jnl`	Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. CoRR Runqian Wang, Soumya Ghosh, David D. Cox, Diego Antognini, Aude Oliva, Rogério Feris, Leonid Karlinsky
2024	J	`jnl`	When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails. CoRR Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri
2023	J	`jnl`	Assessment of Prediction Intervals Using Uncertainty Characteristics Curves. CoRR Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
2023	A*	`conf`	Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. AAAI Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
2023	—	`conf`	Reliable Gradient-free and Likelihood-free Prompt Tuning. EACL (Findings) Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
2023	J	`jnl`	Reliable Gradient-free and Likelihood-free Prompt Tuning. CoRR Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
2022	J	`jnl`	Are you using test log-likelihood correctly? CoRR Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick
2022	A*	`conf`	Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. NeurIPS Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney
2022	J	`jnl`	Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. CoRR Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney
2022	J	`jnl`	Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data. Nat. Comput. Sci. 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
2022	—	`conf`	IoT and E-Learning with the Impact of COVID-19 Pandemic Lockdown on the Undergraduate University Student Blood Pressure Levels. TTSIIT Talib A. Al-Sharify, Zinah A. Alshrefy, Hussein Ali Hussein, Zainab T. Al-Sharify, Helen Onyeaka, Mushtaq T. Al-Sharify, Soumya Ghosh
2022	A	`conf`	Measuring the robustness of Gaussian processes to kernel choice. AISTATS William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick
2022	J	`jnl`	Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. CoRR Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
2022	—	`conf`	Uncertainty Quantification 360: A Hands-on Tutorial. COMAD/CODS Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
2021	J	`jnl`	DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways. IEEE Trans. Vis. Comput. Graph. Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng
2021	—	`conf`	EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders. MLHC Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Cao Xiao, Jimeng Sun
2021	J	`jnl`	Measuring the sensitivity of Gaussian processes to kernel choice. CoRR William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick
2021	A	`conf`	Post-hoc loss-calibration for Bayesian neural networks. UAI Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin
2021	J	`jnl`	Post-hoc loss-calibration for Bayesian neural networks. CoRR Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin
2021	J	`jnl`	Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals. CoRR Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
2021	J	`jnl`	Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI. CoRR Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
2020	A*	`conf`	Approximate Cross-Validation for Structured Models. NeurIPS Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick
2020	J	`jnl`	Approximate Cross-Validation for Structured Models. CoRR Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick
2020	J	`jnl`	Complication Risk Profiling in Diabetes Care: A Bayesian Multi-Task and Feature Relationship Learning Approach. IEEE Trans. Knowl. Data Eng. Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu
2020	J	`jnl`	EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders. CoRR Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Jimeng Sun
2020	A*	`conf`	Model Fusion with Kullback-Leibler Divergence. ICML Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
2020	J	`jnl`	Model Fusion with Kullback-Leibler Divergence. CoRR Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
2020	—	`conf`	Personalized Input-Output Hidden Markov Models for Disease Progression Modeling. MLHC Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh
2019	A*	`conf`	Bayesian Nonparametric Federated Learning of Neural Networks. ICML Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
2019	J	`jnl`	Bayesian Nonparametric Federated Learning of Neural Networks. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
2019	J	`jnl`	DPVis: Visual Exploration of Disease Progression Pathways. CoRR Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng
2019	J	`jnl`	Model Selection in Bayesian Neural Networks via Horseshoe Priors. J. Mach. Learn. Res. Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2019	J	`jnl`	Quality of Uncertainty Quantification for Bayesian Neural Network Inference. CoRR Jiayu Yao, Weiwei Pan, Soumya Ghosh, Finale Doshi-Velez
2019	A*	`conf`	Statistical Model Aggregation via Parameter Matching. NeurIPS Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2019	J	`jnl`	Statistical Model Aggregation via Parameter Matching. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2019	A*	`conf`	Unsupervised Learning with Contrastive Latent Variable Models. AAAI Kristen A. Severson, Soumya Ghosh, Kenney Ng
2018	J	`jnl`	A Review on DNA Based Cryptographic Techniques. Int. J. Netw. Secur. Animesh Hazra, Soumya Ghosh, Sampad Jash
2018	B	`conf`	Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks. FG Ajjen Joshi, Soumya Ghosh, Sarah Gunnery, Linda Tickle-Degnen, Stan Sclaroff, Margrit Betke
2018	A*	`conf`	Early Prediction of Diabetes Complications from Electronic Health Records: A Multi-Task Survival Analysis Approach. AAAI Bin Liu, Ying Li, Zhaonan Sun, Soumya Ghosh, Kenney Ng
2018	J	`jnl`	Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights. CoRR Melanie F. Pradier, Weiwei Pan, Jiayu Yao, Soumya Ghosh, Finale Doshi-Velez
2018	J	`jnl`	Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care. CoRR Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu
2018	A*	`conf`	Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. ICML Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2018	J	`jnl`	Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. CoRR Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2018	J	`jnl`	Unsupervised learning with contrastive latent variable models. CoRR Kristen A. Severson, Soumya Ghosh, Kenney Ng
2017	Misc	`conf`	A Data-Driven Method for Generating Robust Symptom Onset Indicators in Disease Registry Data. AMIA Zhaonan Sun, Ying Li, Soumya Ghosh, Yu Cheng, Amrita Mohan, Cristina Sampaio
2017	—	`conf`	An Exploration of Latent Structure in Observational Huntington's Disease Studies. CRI Soumya Ghosh, Zhaonan Sun, Ying Li, Yu Cheng, Amrita Mohan, Cristina Sampaio, Jianying Hu
2017	—	`conf`	Clinical Trials.Gov: A Topical Analyses. CRI Vibha Anand, Amos Cahan, Soumya Ghosh
2017	—	`conf`	Exploring Factors that Associated with Missing Values in Observational Huntington's Disease Study Data. CRI Zhaonan Sun, Ying Li, Soumya Ghosh, Yu Cheng, Amrita Mohan, Cristina Sampaio, Jianying Hu
2017	—	`conf`	Is There a Priority Shift in Mental Health Clinical Trials? MedInfo Vibha Anand, Soumya Ghosh, Amit Anand
2017	A*	`conf`	Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks. CVPR Ajjen Joshi, Soumya Ghosh, Margrit Betke, Stan Sclaroff, Hanspeter Pfister
2016	A*	`conf`	Assumed Density Filtering Methods for Learning Bayesian Neural Networks. AAAI Soumya Ghosh, Francesco Maria Delle Fave, Jonathan S. Yedidia
2016	—	`conf`	Deep State Space Models for Computational Phenotyping. ICHI Soumya Ghosh, Yu Cheng, Zhaonan Sun
2016	—	`conf`	Graph theoretic interpretation of Bangla traditional grammar. ICON Samir Karmakar, Sayantani Banerjee, Soumya Ghosh
2015	—	`—`	Bayesian Nonparametric Discovery of Layers and Parts from Scenes and Objects. Soumya Ghosh
2014	—	`conf`	Investigation into machine learning algorithms as applied to motor cortex signals for classification of movement stages. EMBC Robert L. Hollingshead, David Putrino, Soumya Ghosh, Tele Tan
2014	A	`conf`	Nonparametric Clustering with Distance Dependent Hierarchies. UAI Soumya Ghosh, Michalis Raptis, Leonid Sigal, Erik B. Sudderth
2012	—	`conf`	From Deformations to Parts: Motion-based Segmentation of 3D Objects. NIPS Soumya Ghosh, Erik B. Sudderth, Matthew Loper, Michael J. Black
2012	A*	`conf`	Nonparametric learning for layered segmentation of natural images. CVPR Soumya Ghosh, Erik B. Sudderth
2011	J	`jnl`	A Granger Causality Measure for Point Process Models of Ensemble Neural Spiking Activity. PLoS Comput. Biol. Sanggyun Kim, David Putrino, Soumya Ghosh, Emery N. Brown
2011	J	`jnl`	Architecture of A Scalable Dynamic Parallel WebCrawler with High Speed Downloadable Capability for a Web Search Engine CoRR Debajyoti Mukhopadhyay, Sajal Mukherjee, Soumya Ghosh, Saheli Kar, Young-Chon Kim
2011	—	`conf`	Spatial distance dependent Chinese restaurant processes for image segmentation. NIPS Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei
2010	A*	`conf`	A segmentation guided label propagation scheme for autonomous navigation. ICRA Soumya Ghosh, Jane Mulligan
2010	J	`jnl`	Automatic Annotation of Planetary Surfaces With Geomorphic Labels. IEEE Trans. Geosci. Remote. Sens. Soumya Ghosh, Tomasz F. Stepinski, Ricardo Vilalta
2009	A	`conf`	A general framework for reconciling multiple weak segmentations of an image. WACV Soumya Ghosh, Joseph J. Pfeiffer III, Jane Mulligan
2009	—	`conf`	Topic model methods for automatically identifying out-of-scope resources. JCDL Steven Bethard, Soumya Ghosh, James H. Martin, Tamara Sumner
2009	B	`conf`	Using weak supervision in learning Gaussian mixture models. IJCNN Soumya Ghosh, Soundararajan Srinivasan, Burton Andrews
2007	J	`jnl`	Machine Learning Tools for Automatic Mapping of Martian Landforms. IEEE Intell. Syst. Tomasz F. Stepinski, Ricardo Vilalta, Soumya Ghosh
2007	A*	`conf`	Machine Learning for Automatic Mapping of Planetary Surfaces. AAAI Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
2006	B	`conf`	Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification. Discovery Science Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta