Garg, Vikas K

17 publications

ICLR 2026 Composition of Pretrained Diffusion Models: A Logic-Based Calculus Peter Blohm, Vikas K Garg

ICLR 2026 Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells Mattie Ji, Indradyumna Roy, Vikas K Garg

ICLR 2026 Frozen Priors, Fluid Forecasts: Prequential Uncertainty for Low-Data Deployment with Pretrained Generative Models Fernando Ruiz-Mazo, Vikas K Garg

ICLR 2026 The Logical Expressiveness of Topological Neural Networks Amirreza Akbari, Amauri H Souza, Vikas K Garg

ICLR 2026 The Spacetime of Diffusion Models: An Information Geometry Perspective Rafal Karczewski, Markus Heinonen, Alison Pouplin, Søren Hauberg, Vikas K Garg

ICML 2025 Devil Is in the Details: Density Guidance for Detail-Aware Generation with Flow Models Rafal Karczewski, Markus Heinonen, Vikas K Garg

NeurIPS 2025 Graph Persistence Goes Spectral Mattie Ji, Amauri H Souza, Vikas K Garg

TMLR 2025 Heterophily-Informed Message Passing Haishan Wang, Arno Solin, Vikas K Garg

NeurIPS 2025 On Topological Descriptors for Graph Products Mattie Ji, Amauri H Souza, Vikas K Garg

ICML 2025 Positional Encoding Meets Persistent Homology on Graphs Yogesh Verma, Amauri H Souza, Vikas K Garg

AISTATS 2025 What Ails Generative Structure-Based Drug Design: Expressivity Is Too Little or Too Much? Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K Garg

ICLRW 2019 Generative Models for Graph-Based Protein Design John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi Jaakkola

UAI 2018 Sparse Multi-Prototype Classification Vikas K. Garg, Lin Xiao, Ofer Dekel

AISTATS 2016 CRAFT: ClusteR-Specific Assorted Feature selecTion Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola

CVPR 2015 DEEP-CARVING: Discovering Visual Attributes by Carving Deep Neural Nets Sukrit Shankar, Vikas K. Garg, Roberto Cipolla

IJCAI 2013 Link Label Prediction in Signed Social Networks Priyanka Agrawal, Vikas K. Garg, Ramasuri Narayanam

AAAI 2013 Online Optimization with Dynamic Temporal Uncertainty: Incorporating Short Term Predictions for Renewable Integration in Intelligent Energy Systems Vikas K. Garg, T. S. Jayram, Balakrishnan Narayanaswamy