Bohang Zhang
16 papers · 2020–2025 · 3 venues · across top CS/AI venues
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Achievements
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(11)
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(5)
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(3)
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Venues
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Research topics
Machine Learning
(14)
Deep Learning
(10)
Optimization & Theory
(10)
Architectures
(9)
Core Methods
(7)
Artificial Intelligence
(5)
Core AI
(5)
Natural Language Processing
(3)
Application Areas
(3)
Resources & Methods
(2)
Techniques
(2)
Healthcare & Medicine
(1)
Knowledge & Reasoning
(1)
Mathematics & Optimization
(1)
Applications
(1)
Keywords
graph neural network
(5)
certified robustness
(3)
lipschitz constant
(3)
lipchitz constant
(2)
convergence analysis
(2)
dynamic programming
(2)
homomorphism expressivity
(2)
neural network
(2)
non-convex optimization
(2)
stochastic gradient descent
(2)
expressive power
(2)
subgraph counting
(2)
weisfeiler-lehman test
(2)
graph structure
(1)
graph representation
(1)
adversarial training
(1)
benchmark evaluation
(1)
transformer architecture
(1)
mathematical reasoning
(1)
signal-to-noise ratio
(1)
Papers
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
ICML 2025
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
ICLR 2025
How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
ICLR 2025
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
ICLR 2024
Can Graph Learning Improve Planning in LLM-based Agents?
NeurIPS 2024
Do Efficient Transformers Really Save Computation?
ICML 2024
On the Expressive Power of Spectral Invariant Graph Neural Networks
ICML 2024
A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests
ICML 2023
Finding Generalization Measures by Contrasting Signal and Noise
ICML 2023
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
ICLR 2023
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
NeurIPS 2023
Boosting the Certified Robustness of L-infinity Distance Nets
ICLR 2022
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective
NeurIPS 2022
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
NeurIPS 2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
ICML 2021
Improved Analysis of Clipping Algorithms for Non-convex Optimization
NeurIPS 2020