Kartik Ahuja
22 papers · 2017–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (6) πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π Academic Marathon (8)
π
Cross-Pollinator
(14)
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Renaissance Researcher
(8)
πΊοΈ
Taxonomy Completionist
(10)
π
Triple Crown
π
Keyword Champion
ποΈ
Keyword Collector
(75)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(22)
π₯
Unstoppable
(6)
β
The Questioner
(3)
Conferences
ICML (6)
NIPS (6)
ICLR (4)
AISTATS (3)
CLEAR (2)
UAI (1)
Top co-authors
Keywords
out-of-distribution generalization
(5)
invariant risk minimization
(5)
representation learning
(3)
domain generalization
(3)
latent variable
(2)
nash equilibrium
(2)
causal representation learning
(2)
spurious correlation
(2)
latent factor
(2)
causal inference
(2)
risk management
(1)
information bottleneck
(1)
causal discovery
(1)
visual question answering
(1)
independent component analysis
(1)
adversarial robustness
(1)
game theory
(1)
model merging
(1)
domain adaptation
(1)
feature learning
(1)
Papers
DRoP: Distributionally Robust Data Pruning
ICLR 2025
Compositional Risk Minimization
ICML 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
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
ICML 2023
Reusable Slotwise Mechanisms
NIPS 2023
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
NIPS 2023
Interventional Causal Representation Learning
ICML 2023
Why does Throwing Away Data Improve Worst-Group Error?
ICML 2023
Weakly Supervised Representation Learning with Sparse Perturbations
NIPS 2022
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
Conditionally independent data generation
UAI 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
NIPS 2021
Adversarial Feature Desensitization
NIPS 2021
Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
AISTATS 2021
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
ICLR 2021
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
ICML 2021
Invariant Risk Minimization Games
ICML 2020
DPSCREEN: Dynamic Personalized Screening
NIPS 2017