Bao Wang
18 papers · 2018–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (30) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π
Triple Crown
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Grand Slam
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Keyword Pioneer
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(100)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(16)
Optimization & Theory Β· Machine Learning
(12)
Deep Learning
(11)
Architectures
(8)
Mathematics & Optimization
(4)
Core Methods
(4)
Optimization
(4)
Learning Types Β· Machine Learning
(3)
Models
(3)
Artificial Intelligence
(2)
Learning Types Β· Deep Learning
(2)
Optimization & Theory Β· Deep Learning
(2)
Techniques
(2)
Computer Vision
(1)
Reinforcement Learning
(1)
Keywords
graph neural network
(4)
stochastic gradient descent
(3)
decentralized optimization
(2)
non-convex optimization
(2)
monotone operator
(2)
generative model
(2)
deep neural network
(2)
node classification
(2)
temporal difference learning
(1)
label propagation
(1)
robust optimization
(1)
function approximation
(1)
attention mechanism
(1)
convergence analysis
(1)
image classification
(1)
ensemble learning
(1)
deep learning
(1)
manifold learning
(1)
adversarial learning
(1)
flow matching
(1)
Papers
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
ICLR 2025
Improving Flow Matching by Aligning Flow Divergence
ICML 2025
Investigating the Role of Weight Decay in Enhancing Nonconvex SGD
CVPR 2025
An Explicit Frame Construction for Normalizing 3D Point Clouds
ICML 2024
Efficient Score Matching with Deep Equilibrium Layers
ICLR 2024
Monotone Operator Theory-Inspired Message Passing for Learning Long-Range Interaction on Graphs
AISTATS 2024
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
ICLR 2024
Implicit Graph Neural Networks: A Monotone Operator Viewpoint
ICML 2023
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions
ICML 2023
Adaptive Random Walk Gradient Descent for Decentralized Optimization
ICML 2022
Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks
NeurIPS 2022
GRAND++: Graph Neural Diffusion with A Source Term
ICLR 2022
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention
NeurIPS 2021
Heavy Ball Neural Ordinary Differential Equations
NeurIPS 2021
Stability and Generalization of Decentralized Stochastic Gradient Descent
AAAI 2021
MomentumRNN: Integrating Momentum into Recurrent Neural Networks
NeurIPS 2020
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies
NeurIPS 2019
Deep Neural Nets with Interpolating Function as Output Activation
NeurIPS 2018