Vikas Garg
32 papers · 2013–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (4) π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer π Academic Marathon (12)
π£
Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(56)
π
Conference Polyglot
(4)
π±
Topic Pioneer
π§¬
Topic Evolution
π
Keyword Champion
(2)
π
Triple Crown
ποΈ
Keyword Collector
(116)
β‘
Prolific Year
(7)
π
Century Club
(32)
π₯
Unstoppable
(10)
π
Trend Setter
β
The Questioner
(3)
Conferences
NIPS (18)
ICLR (7)
ICML (6)
AISTATS (1)
Top co-authors
Keywords
graph neural network
(9)
message passing
(4)
molecular generation
(3)
generalization bound
(3)
boolean relaxation
(2)
graph generation
(2)
protein design
(2)
persistent homology
(2)
game theory
(2)
multi-agent system
(2)
topological feature
(2)
graph theory
(1)
binary classification
(1)
graph classification
(1)
feature selection
(1)
matrix factorization
(1)
domain generalization
(1)
representation learning
(1)
structured prediction
(1)
pac learning
(1)
Papers
Generalization and Distributed Learning of GFlowNets
ICLR 2025
Diffusion Models as Cartoonists: The Curious Case of High Density Regions
ICLR 2025
When do GFlowNets learn the right distribution?
ICLR 2025
Robust Simulation-Based Inference under Missing Data via Neural Processes
ICLR 2025
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
ICLR 2025
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
ICLR 2025
Topological Neural Networks go Persistent, Equivariant, and Continuous
ICML 2024
What do Graph Neural Networks learn? Insights from Tropical Geometry
NIPS 2024
Algebraic Positional Encodings
NIPS 2024
Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
NIPS 2024
Diffusion Twigs with Loop Guidance for Conditional Graph Generation
NIPS 2024
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
ICLR 2024
On the Generalization of Equivariant Graph Neural Networks
ICML 2024
Going beyond persistent homology using persistent homology
NIPS 2023
AbODE: Ab initio antibody design using conjoined ODEs
ICML 2023
Compositional Sculpting of Iterative Generative Processes
NIPS 2023
Are GANs overkill for NLP?
NIPS 2022
Provably expressive temporal graph networks
NIPS 2022
Symmetry-induced Disentanglement on Graphs
NIPS 2022
Modular Flows: Differential Molecular Generation
NIPS 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
NIPS 2019
Solving graph compression via optimal transport
NIPS 2019
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
NIPS 2019
Supervising Unsupervised Learning
NIPS 2018
Learning SMaLL Predictors
NIPS 2018
Local Aggregative Games
NIPS 2017
Learning Tree Structured Potential Games
NIPS 2016
Multiresolution Matrix Factorization
ICML 2014
Adaptivity to Local Smoothness and Dimension in Kernel Regression
NIPS 2013