Jiashuo Liu
17 papers · 2021–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (25) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π Grand Slam
π€
Dynamic Duo
(15)
π
Triple Crown
ποΈ
Keyword Collector
(65)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(17)
Application Areas
(14)
Learning Types Β· Machine Learning
(7)
Optimization & Theory
(7)
Artificial Intelligence
(4)
Core AI
(4)
Core Methods
(4)
Deep Learning
(3)
Mathematics & Optimization
(2)
Learning Types Β· Deep Learning
(2)
Computer Vision
(1)
Analysis
(1)
Architectures
(1)
Mathematics
(1)
Optimization
(1)
Keywords
out-of-distribution generalization
(8)
distribution shift
(7)
domain generalization
(5)
gradient flow
(3)
invariant learning
(3)
distributional shift
(3)
causal inference
(2)
covariate shift
(2)
distributionally robust optimization
(2)
optimal transport
(2)
latent heterogeneity
(2)
label shift
(1)
domain adaptation
(1)
information maximization
(1)
empirical risk minimization
(1)
generative augmentation
(1)
robust optimization
(1)
generalization
(1)
generalization bound
(1)
robust learning
(1)
Papers
Error Slice Discovery via Manifold Compactness
AAAI 2026
Going Beyond Static: Understanding Shifts with Time-Series Attribution
ICLR 2025
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
ICML 2025
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
NeurIPS 2024
Distributionally Generative Augmentation for Fair Facial Attribute Classification
CVPR 2024
Domain-wise Data Acquisition to Improve Performance under Distribution Shift
ICML 2024
Enhancing Distributional Stability among Sub-populations
AISTATS 2024
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
ICML 2024
Rethinking the Evaluation Protocol of Domain Generalization
CVPR 2024
Stability Evaluation through Distributional Perturbation Analysis
ICML 2024
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
ICLR 2024
Measure the Predictive Heterogeneity
ICLR 2023
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
NeurIPS 2023
Distributionally Robust Optimization with Data Geometry
NeurIPS 2022
Heterogeneous Risk Minimization
ICML 2021
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space
NeurIPS 2021
Stable Adversarial Learning under Distributional Shifts
AAAI 2021