Tailin Wu
19 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (5) π Cross-Pollinator (11)
πΊοΈ
Taxonomy Completionist
(33)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π
Grand Slam
π
Conference Pioneer
β‘
Prolific Year
(8)
ποΈ
Keyword Collector
(51)
π
Century Club
(19)
Conferences
ICLR (8)
NIPS (5)
ICML (3)
AAAI (2)
UAI (1)
Top co-authors
Keywords
information bottleneck
(2)
graph neural network
(2)
representation learning
(2)
partial differential equation
(2)
graph theory
(1)
uncertainty quantification
(1)
zero-shot learning
(1)
latent space
(1)
mutual information
(1)
trajectory optimization
(1)
graph modularity
(1)
diffusion model
(1)
phase transition
(1)
inverse problem
(1)
surrogate model
(1)
hypothesis testing
(1)
normalizing flow
(1)
energy-based model
(1)
optimal control
(1)
adversarial robustness
(1)
Papers
On the Guidance of Flow Matching
ICML 2025
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
ICML 2025
M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation
ICML 2025
Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization
AAAI 2025
EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow
ICLR 2025
Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model
ICLR 2025
Wavelet Diffusion Neural Operator
ICLR 2025
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems
ICLR 2025
DiffPhyCon: A Generative Approach to Control Complex Physical Systems
NIPS 2024
BENO: Boundary-embedded Neural Operators for Elliptic PDEs
ICLR 2024
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
AAAI 2024
Compositional Generative Inverse Design
ICLR 2024
Learning Controllable Adaptive Simulation for Multi-resolution Physics
ICLR 2023
Learning to Accelerate Partial Differential Equations via Latent Global Evolution
NIPS 2022
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time
NIPS 2022
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
NIPS 2020
Graph Information Bottleneck
NIPS 2020
Phase Transitions for the Information Bottleneck in Representation Learning
ICLR 2020
Learnability for the Information Bottleneck
UAI 2019