Kartik Ahuja
22 papers · 2017–2025 · 6 venues · across top CS/AI venues
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Achievements
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(6)
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(3)
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Conference Pioneer
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Research topics
Machine Learning
(22)
Learning Types
(13)
Application Areas
(12)
Artificial Intelligence
(10)
Core Methods
(10)
Core AI
(8)
Optimization & Theory
(5)
Learning Paradigms
(3)
Knowledge & Reasoning
(2)
Reasoning
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Deep Learning
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Keywords
out-of-distribution generalization
(6)
invariant risk minimization
(6)
domain generalization
(4)
representation learning
(3)
latent variable
(3)
causal inference
(2)
feature learning
(2)
spurious correlation
(2)
latent factor
(2)
causal representation learning
(2)
nash equilibrium
(2)
distribution shift
(2)
empirical risk minimization
(2)
causal discovery
(1)
information bottleneck
(1)
adversarial robustness
(1)
independent component analysis
(1)
game theory
(1)
neural network pruning
(1)
domain adaptation
(1)
Papers
Compositional Risk Minimization
ICML 2025
DRoP: Distributionally Robust Data Pruning
ICLR 2025
Context is Environment
ICLR 2024
Multi-Domain Causal Representation Learning via Weak Distributional Invariances
AISTATS 2024
On the Identifiability of Quantized Factors
CLeaR 2024
Interventional Causal Representation Learning
ICML 2023
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
NeurIPS 2023
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
ICML 2023
Reusable Slotwise Mechanisms
NeurIPS 2023
Why does Throwing Away Data Improve Worst-Group Error?
ICML 2023
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge
AISTATS 2022
Properties from mechanisms: an equivariance perspective on identifiable representation learning
ICLR 2022
Towards efficient representation identification in supervised learning
CLeaR 2022
Weakly Supervised Representation Learning with Sparse Perturbations
NeurIPS 2022
Adversarial Feature Desensitization
NeurIPS 2021
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
ICML 2021
Conditionally independent data generation
UAI 2021
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
ICLR 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
NeurIPS 2021
Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
AISTATS 2021
Invariant Risk Minimization Games
ICML 2020
DPSCREEN: Dynamic Personalized Screening
NeurIPS 2017