Pratik Chaudhari
25 papers · 2018–2026 · 10 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7)
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(2)
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(24)
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(8)
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The Questioner
(4)
Conferences
ICLR (7)
ICML (6)
NIPS (5)
AAAI (1)
CORL (1)
CVPR (1)
ICCV (1)
MIDL (1)
RSS (1)
UAI (1)
Top co-authors
Keywords
representation learning
(3)
transfer learning
(3)
information geometry
(3)
semi-supervised learning
(2)
domain shift
(2)
extrapolation error
(2)
data augmentation
(2)
eigenvalue spectrum
(2)
fisher information matrix
(2)
offline reinforcement learning
(2)
ensemble learning
(1)
variational inference
(1)
feature learning
(1)
bayesian inference
(1)
domain generalization
(1)
policy optimization
(1)
reinforcement learning
(1)
model distillation
(1)
knowledge distillation
(1)
optimal transport
(1)
Papers
The LUMirage: An independent evaluation of zero-shot performance in the LUMIR challenge
MIDL 2026
From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations
ICCV 2025
AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents
ICLR 2025
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
ICLR 2024
Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation
RSS 2024
Deep Learning in Medical Image Registration: Magic or Mirage?
NIPS 2024
Prospective Learning: Learning for a Dynamic Future
NIPS 2024
The Value of Out-of-Distribution Data
ICML 2023
A Picture of the Space of Typical Learnable Tasks
ICML 2023
Budgeting Counterfactual for Offline RL
NIPS 2023
Beyond mAP: Towards Better Evaluation of Instance Segmentation
CVPR 2023
Does the Geometry of the Data Control the Geometry of Neural Predictions? (Student Abstract)
AAAI 2022
Does the Data Induce Capacity Control in Deep Learning?
ICML 2022
Model Zoo: A Growing Brain That Learns Continually
ICLR 2022
Deep Reference Priors: What is the best way to pretrain a model?
ICML 2022
Continuous Doubly Constrained Batch Reinforcement Learning
NIPS 2021
An Information-Geometric Distance on the Space of Tasks
ICML 2021
Meta-Q-Learning
ICLR 2020
BayesRace: Learning to race autonomously using prior experience
CORL 2020
A Baseline for Few-Shot Image Classification
ICLR 2020
Rethinking the Hyperparameters for Fine-tuning
ICLR 2020
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
NIPS 2020
A Free-Energy Principle for Representation Learning
ICML 2020
P3O: Policy-on Policy-off Policy Optimization
UAI 2019
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
ICLR 2018