Jiashuo Liu
17 papers · 2021–2026 · 6 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (10) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (5)
🏃
Academic Marathon
(5)
🏆
Grand Slam
👑
Triple Crown
🤝
Dynamic Duo
(14)
🔥
Unstoppable
(5)
💎
Century Club
(16)
⚡
Prolific Year
(8)
Conferences
ICML (5)
NIPS (4)
ICLR (3)
AAAI (2)
CVPR (2)
AISTATS (1)
Top co-authors
Keywords
out-of-distribution generalization
(5)
domain generalization
(5)
distribution shift
(4)
invariant learning
(3)
distributional shift
(3)
distributionally robust optimization
(2)
covariate shift
(2)
latent heterogeneity
(2)
robust learning
(1)
uncertainty set
(1)
gradient flow
(1)
bias mitigation
(1)
spurious correlation
(1)
tabular datum
(1)
self-supervised pretraining
(1)
concept shift
(1)
manifold geometry
(1)
evaluation protocol
(1)
model interpretation
(1)
subgroup discovery
(1)
Papers
Error Slice Discovery via Manifold Compactness
AAAI 2026
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
ICML 2025
Going Beyond Static: Understanding Shifts with Time-Series Attribution
ICLR 2025
Domain-wise Data Acquisition to Improve Performance under Distribution Shift
ICML 2024
Rethinking the Evaluation Protocol of Domain Generalization
CVPR 2024
Distributionally Generative Augmentation for Fair Facial Attribute Classification
CVPR 2024
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
ICML 2024
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
ICLR 2024
Enhancing Distributional Stability among Sub-populations
AISTATS 2024
Stability Evaluation through Distributional Perturbation Analysis
ICML 2024
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
NIPS 2024
Measure the Predictive Heterogeneity
ICLR 2023
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
NIPS 2023
Distributionally Robust Optimization with Data Geometry
NIPS 2022
Heterogeneous Risk Minimization
ICML 2021
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space
NIPS 2021
Stable Adversarial Learning under Distributional Shifts
AAAI 2021