Vikas Garg
32 papers · 2013–2025 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (59) π Academic Marathon Β· Half π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(11)
π§¬
Topic Evolution
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Keyword Champion
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Triple Crown
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Renaissance Researcher
(6)
π₯
Unstoppable Β· Silver
β
The Questioner
(3)
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Prolific Year Β· Productive
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Century Club Β· Bronze
ποΈ
Keyword Collector
(150)
Venues
Top co-authors
Research topics
Machine Learning
(25)
Deep Learning
(22)
Core Methods
(16)
Architectures
(14)
Models
(12)
Optimization & Theory
(11)
Artificial Intelligence
(10)
Core AI
(9)
Mathematics & Optimization
(6)
Optimization
(6)
Learning Types Β· Machine Learning
(5)
Learning Types Β· Deep Learning
(5)
Application Areas
(2)
Mathematics
(2)
Computer Science
(1)
Keywords
graph neural network
(11)
generalization bound
(5)
message passing
(4)
persistent homology
(3)
molecular generation
(3)
graph generation
(3)
multi-agent system
(2)
game theory
(2)
generative flow network
(2)
topological feature
(2)
generative model
(2)
boolean relaxation
(2)
protein design
(2)
diffusion model
(2)
graph theory
(1)
feature selection
(1)
binary classification
(1)
matrix factorization
(1)
structured prediction
(1)
domain generalization
(1)
Papers
Diffusion Models as Cartoonists: The Curious Case of High Density Regions
ICLR 2025
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
ICLR 2025
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
ICLR 2025
Generalization and Distributed Learning of GFlowNets
ICLR 2025
Robust Simulation-Based Inference under Missing Data via Neural Processes
ICLR 2025
When do GFlowNets learn the right distribution?
ICLR 2025
Algebraic Positional Encodings
NeurIPS 2024
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
ICLR 2024
Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
NeurIPS 2024
Diffusion Twigs with Loop Guidance for Conditional Graph Generation
NeurIPS 2024
On the Generalization of Equivariant Graph Neural Networks
ICML 2024
Topological Neural Networks go Persistent, Equivariant, and Continuous
ICML 2024
What do Graph Neural Networks learn? Insights from Tropical Geometry
NeurIPS 2024
AbODE: Ab initio antibody design using conjoined ODEs
ICML 2023
Compositional Sculpting of Iterative Generative Processes
NeurIPS 2023
Going beyond persistent homology using persistent homology
NeurIPS 2023
Are GANs overkill for NLP?
NeurIPS 2022
Modular Flows: Differential Molecular Generation
NeurIPS 2022
Provably expressive temporal graph networks
NeurIPS 2022
Symmetry-induced Disentanglement on Graphs
NeurIPS 2022
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
AISTATS 2021
Generalization and Representational Limits of Graph Neural Networks
ICML 2020
Predicting deliberative outcomes
ICML 2020
Generative Models for Graph-Based Protein Design
NeurIPS 2019
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
NeurIPS 2019
Solving graph compression via optimal transport
NeurIPS 2019
Learning SMaLL Predictors
NeurIPS 2018
Supervising Unsupervised Learning
NeurIPS 2018
Local Aggregative Games
NeurIPS 2017
Learning Tree Structured Potential Games
NeurIPS 2016
Multiresolution Matrix Factorization
ICML 2014
Adaptivity to Local Smoothness and Dimension in Kernel Regression
NeurIPS 2013