Derek Lim
16 papers · 2020–2026 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (29) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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(80)
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Research topics
Machine Learning
(15)
Deep Learning
(12)
Architectures
(11)
Core Methods
(11)
Optimization & Theory Β· Machine Learning
(8)
Artificial Intelligence
(4)
Core AI
(3)
Mathematics & Optimization
(2)
Mathematics
(2)
Optimization & Theory Β· Deep Learning
(2)
Techniques
(2)
Natural Language Processing
(1)
Applications
(1)
Learning Paradigms
(1)
Learning Types
(1)
Keywords
graph neural network
(9)
expressive power
(3)
message passing
(2)
generative model
(2)
equivariant learning
(2)
self-supervised learning
(1)
density estimation
(1)
manifold learning
(1)
graph representation
(1)
model merging
(1)
group theory
(1)
neural network optimization
(1)
neural architecture
(1)
optimization
(1)
embedding space
(1)
optimization landscape
(1)
graph representation learning
(1)
output distribution
(1)
geometric structure
(1)
attention mechanism
(1)
Papers
Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions
AAAI 2026
A Canonicalization Perspective on Invariant and Equivariant Learning
NeurIPS 2024
Graph Metanetworks for Processing Diverse Neural Architectures
ICLR 2024
Position: Future Directions in the Theory of Graph Machine Learning
ICML 2024
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
ICLR 2024
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
NeurIPS 2024
Equivariant Polynomials for Graph Neural Networks
ICML 2023
Expressive Sign Equivariant Networks for Spectral Geometric Learning
NeurIPS 2023
Graph Inductive Biases in Transformers without Message Passing
ICML 2023
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
ICLR 2023
The Power of Recursion in Graph Neural Networks for Counting Substructures
AISTATS 2023
Equivariant Subgraph Aggregation Networks
ICLR 2022
Understanding Doubly Stochastic Clustering
ICML 2022
Equivariant Manifold Flows
NeurIPS 2021
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
NeurIPS 2021
Neural Manifold Ordinary Differential Equations
NeurIPS 2020