Weinan E
16 papers · 2016–2026 · 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 (28) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π§¬
Topic Evolution
ποΈ
Keyword Collector
(84)
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Silver
π
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory Β· Machine Learning
(11)
Deep Learning
(7)
Artificial Intelligence
(4)
Core AI
(4)
Techniques
(4)
Architectures
(3)
Core Methods
(3)
Optimization & Theory Β· Deep Learning
(3)
Interdisciplinary
(2)
Application Areas
(2)
Science
(2)
Computer Vision
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Keywords
stochastic gradient descent
(4)
approximation theory
(3)
stochastic differential equation
(3)
neural network optimization
(2)
optimal control
(2)
deep learning
(2)
stochastic modified equation
(2)
recurrent neural network
(2)
weak approximation
(2)
flat minima
(2)
video generation
(1)
sharpness-aware minimization
(1)
feature extraction
(1)
theoretical analysis
(1)
sequence modeling
(1)
code generation
(1)
machine learning
(1)
information retrieval
(1)
gradient descent
(1)
attention mechanism
(1)
Papers
TeachMaster: Generative Teaching via Code
ACL 2026
PaSa: An LLM Agent for Comprehensive Academic Paper Search
ACL 2025
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training
ICML 2025
Exploring Molecular Pretraining Model at Scale
NeurIPS 2024
Improving Generalization and Convergence by Enhancing Implicit Regularization
NeurIPS 2024
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling
NeurIPS 2024
An Iteratively Parallel Generation Method with the Pre-Filling Strategy for Document-level Event Extraction
EMNLP 2023
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
JMLR 2022
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
ICLR 2021
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning
NeurIPS 2020
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations
JMLR 2019
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems
NeurIPS 2018
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
NeurIPS 2018
Maximum Principle Based Algorithms for Deep Learning
JMLR 2018
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms
ICML 2017
Multiscale Adaptive Representation of Signals: I. The Basic Framework
JMLR 2016