Soumya Ghosh
21 papers · 2011–2025 · 10 venues · across top CS/AI venues
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Achievements
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Research topics
Machine Learning
(19)
Artificial Intelligence
(15)
Optimization & Theory
(10)
Bayesian & Probabilistic Β· Artificial Intelligence
(8)
Learning Types
(8)
Core AI
(7)
Core Methods
(7)
Deep Learning
(6)
Bayesian & Probabilistic Β· Machine Learning
(6)
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Keywords
bayesian neural network
(4)
uncertainty quantification
(4)
bayesian nonparametrics
(3)
variational inference
(3)
large language model
(3)
gaussian process
(2)
unsupervised learning
(2)
model selection
(2)
latent variable model
(2)
nonparametric bayesian
(2)
out-of-distribution detection
(2)
chinese restaurant process
(2)
transfer learning
(2)
bayesian inference
(2)
federated learning
(2)
horseshoe prior
(2)
pose estimation
(1)
image segmentation
(1)
bayesian learning
(1)
contrastive learning
(1)
Papers
Multi-Level Explanations for Generative Language Models
ACL 2025
Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning
NeurIPS 2024
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
NeurIPS 2024
Thermometer: Towards Universal Calibration for Large Language Models
ICML 2024
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model
AAAI 2023
Reliable Gradient-free and Likelihood-free Prompt Tuning
EACL 2023
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
NeurIPS 2022
Measuring the robustness of Gaussian processes to kernel choice
AISTATS 2022
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders
MLHC 2021
Post-hoc loss-calibration for Bayesian neural networks
UAI 2021
Approximate Cross-Validation for Structured Models
NeurIPS 2020
Model Fusion with Kullback-Leibler Divergence
ICML 2020
Personalized Input-Output Hidden Markov Models for Disease Progression Modeling
MLHC 2020
Bayesian Nonparametric Federated Learning of Neural Networks
ICML 2019
Model Selection in Bayesian Neural Networks via Horseshoe Priors
JMLR 2019
Statistical Model Aggregation via Parameter Matching
NeurIPS 2019
Unsupervised Learning with Contrastive Latent Variable Models
AAAI 2019
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
ICML 2018
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks
CVPR 2017
From Deformations to Parts: Motion-based Segmentation of 3D Objects
NeurIPS 2012
Spatial distance dependent Chinese restaurant processes for image segmentation
NeurIPS 2011