Vikas Garg - RankMe

50 papers A* 21Journal 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Canonicalizing Multimodal Contrastive Representation Learning. CoRR Sharut Gupta, Sanyam Kansal, Stefanie Jegelka, Phillip Isola, Vikas Garg
2025	J	`jnl`	AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Control. CoRR Shao-Yi Yu, Jen-Wei Wang, Maya Horii, Vikas Garg, Tarek Zohdi
2025	J	`jnl`	Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models. CoRR Rafal Karczewski, Markus Heinonen, Vikas Garg
2025	A*	`conf`	Diffusion Models as Cartoonists: The Curious Case of High Density Regions. ICLR Rafal Karczewski, Markus Heinonen, Vikas Garg
2025	A*	`conf`	E(3)-equivariant models cannot learn chirality: Field-based molecular generation. ICLR Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki
2025	A*	`conf`	Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models. ICLR Najwa Laabid, Severi Rissanen, Markus Heinonen, Arno Solin, Vikas Garg
2025	A*	`conf`	Generalization and Distributed Learning of GFlowNets. ICLR Tiago Silva, Amauri H. Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita
2025	J	`jnl`	Graph Persistence goes Spectral. CoRR Mattie Ji, Amauri H. Souza, Vikas Garg
2025	J	`jnl`	Heat Kernel Goes Topological. CoRR Maximilian Krahn, Vikas Garg
2025	J	`jnl`	Heterophily-informed Message Passing. CoRR Haishan Wang, Arno Solin, Vikas Garg
2025	J	`jnl`	Let Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation. CoRR Yogesh Verma, Markus Heinonen, Vikas Garg
2025	J	`jnl`	On topological descriptors for graph products. CoRR Mattie Ji, Amauri H. Souza, Vikas Garg
2025	J	`jnl`	Positional Encoding meets Persistent Homology on Graphs. CoRR Yogesh Verma, Amauri H. Souza, Vikas Garg
2025	A*	`conf`	Robust Simulation-Based Inference under Missing Data via Neural Processes. ICLR Yogesh Verma, Ayush Bharti, Vikas Garg
2025	J	`jnl`	Robust Simulation-Based Inference under Missing Data via Neural Processes. CoRR Yogesh Verma, Ayush Bharti, Vikas Garg
2025	J	`jnl`	Spacetime Geometry of Denoising in Diffusion Models. CoRR Rafal Karczewski, Markus Heinonen, Alison Pouplin, Søren Hauberg, Vikas Garg
2025	A*	`conf`	When do GFlowNets learn the right distribution? ICLR Tiago da Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H. Souza, Vikas Garg, Samuel Kaski, Diego Mesquita
2024	J	`jnl`	ACE: Abstractions for Communicating Efficiently. CoRR Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Vikas Garg, Moa Johansson
2024	A*	`conf`	Algebraic Positional Encodings. NeurIPS Konstantinos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg
2024	J	`jnl`	Alignment is Key for Applying Diffusion Models to Retrosynthesis. CoRR Najwa Laabid, Severi Rissanen, Markus Heinonen, Arno Solin, Vikas Garg
2024	A*	`conf`	ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs. ICLR Yogesh Verma, Markus Heinonen, Vikas Garg
2024	J	`jnl`	ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs. CoRR Yogesh Verma, Markus Heinonen, Vikas Garg
2024	A*	`conf`	Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond. NeurIPS Kirill Brilliantov, Amauri H. Souza, Vikas Garg
2024	J	`jnl`	Diffusion Models as Cartoonists! The Curious Case of High Density Regions. CoRR Rafal Karczewski, Markus Heinonen, Vikas Garg
2024	A*	`conf`	Diffusion Twigs with Loop Guidance for Conditional Graph Generation. NeurIPS Giangiacomo Mercatali, Yogesh Verma, André Freitas, Vikas Garg
2024	J	`jnl`	Diffusion Twigs with Loop Guidance for Conditional Graph Generation. CoRR Giangiacomo Mercatali, Yogesh Verma, André Freitas, Vikas Garg
2024	J	`jnl`	Employing Federated Learning for Training Autonomous HVAC Systems. CoRR Fredrik Hagström, Vikas Garg, Fabricio Oliveira
2024	J	`jnl`	Field-based Molecule Generation. CoRR Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki
2024	A*	`conf`	Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces. CHI Yue Jiang, Changkong Zhou, Vikas Garg, Antti Oulasvirta
2024	J	`jnl`	Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces. CoRR Yue Jiang, Changkong Zhou, Vikas Garg, Antti Oulasvirta
2024	J	`jnl`	Heteroscedastic Preferential Bayesian Optimization with Informative Noise Distributions. CoRR Marshal Arijona Sinaga, Julien Martinelli, Vikas Garg, Samuel Kaski
2024	A*	`conf`	On the Generalization of Equivariant Graph Neural Networks. ICML Rafal Karczewski, Amauri H. Souza, Vikas Garg
2024	A*	`conf`	Topological Neural Networks go Persistent, Equivariant, and Continuous. ICML Yogesh Verma, Amauri H. Souza, Vikas Garg
2024	J	`jnl`	Topological Neural Networks go Persistent, Equivariant, and Continuous. CoRR Yogesh Verma, Amauri H. Souza, Vikas Garg
2024	J	`jnl`	What Ails Generative Structure-based Drug Design: Too Little or Too Much Expressivity? CoRR Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas Garg
2024	A*	`conf`	What do Graph Neural Networks learn? Insights from Tropical Geometry. NeurIPS Tuan Anh Pham, Vikas Garg
2023	J	`jnl`	AbODE: Ab Initio Antibody Design using Conjoined ODEs. CoRR Yogesh Verma, Markus Heinonen, Vikas Garg
2023	A*	`conf`	AbODE: Ab initio antibody design using conjoined ODEs. ICML Yogesh Verma, Markus Heinonen, Vikas Garg
2023	J	`jnl`	Algebraic Positional Encodings. CoRR Konstantinos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg
2023	A*	`conf`	Compositional Sculpting of Iterative Generative Processes. NeurIPS Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola
2023	J	`jnl`	Compositional Sculpting of Iterative Generative Processes. CoRR Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola
2023	A*	`conf`	Going beyond persistent homology using persistent homology. NeurIPS Johanna Immonen, Amauri H. Souza, Vikas Garg
2023	J	`jnl`	Going beyond persistent homology using persistent homology. CoRR Johanna Immonen, Amauri H. Souza, Vikas Garg
2022	A*	`conf`	Are GANs overkill for NLP? NeurIPS David Alvarez-Melis, Vikas Garg, Adam Kalai
2022	A*	`conf`	Modular Flows: Differential Molecular Generation. NeurIPS Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg
2022	J	`jnl`	Modular Flows: Differential Molecular Generation. CoRR Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg
2022	A*	`conf`	Provably expressive temporal graph networks. NeurIPS Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
2022	J	`jnl`	Provably expressive temporal graph networks. CoRR Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
2022	A*	`conf`	Symmetry-induced Disentanglement on Graphs. NeurIPS Giangiacomo Mercatali, André Freitas, Vikas Garg
2022	J	`jnl`	Why GANs are overkill for NLP. CoRR David Alvarez-Melis, Vikas Garg, Adam Tauman Kalai