Vikas Garg
- Generalization and Representational Limits of Graph Neural Networks
2020/02/14 by Vikas Garg, Stefanie Jegelka, Garg, Vikas K. +3 · 12 citations
Computer Science · #Advanced Graph Neural Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
- Topological Neural Networks go Persistent, Equivariant, and Continuous
2024/06/05 by Yogesh Verma, Amauri H Souza, Verma, Yogesh +3 · 6 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
- E(3)-equivariant models cannot learn chirality: Field-based molecular generation
2024/02/24 by Alexandru Dumitrescu, Dani Korpela, Dumitrescu, Alexandru +11 · 3 citations
Engineering · #Molecular Communication and Nanonetworks #Molecular Junctions and Nanostructures #Nanotechnology research and applications
- The Spacetime of Diffusion Models: An Information Geometry Perspective
2025/05/23 by Rafał Karczewski, Markus Heinonen, Karczewski, Rafał +7 · 3 voices · 3 citations
Computer Science · Mathematics · Physics and Astronomy · #Morphological variations and asymmetry #Statistical Mechanics and Entropy #Topological and Geometric Data Analysis #cs.LG
- Diffusion Models as Cartoonists: The Curious Case of High Density Regions
2024/11/02 by Rafał Karczewski, Karczewski, Rafał, Markus Heinonen +3 · 4 citations
Social Sciences · #Computer Vision and Pattern Recognition (cs.CV) #Cultural Industries and Urban Development #FOS: Computer and information sciences #Machine Learning (cs.LG) #Political Systems and Governance #Regional Development and Policy
- Learn to Expect the Unexpected: Probably Approximately Correct Domain\n Generalization
2020/02/13 by Vikas Garg, Garg, Vikas K., Adam Tauman Kalai +5 · 1 citation
Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Multimodal Machine Learning Applications #Reservoir Engineering and Simulation Methods
- Supervising Unsupervised Learning
2017/09/14 by Vikas Garg, Garg, Vikas K., Adam Tauman Kalai +1 · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Algebraic Positional Encodings
2023/12/26 by Konstantinos Kogkalidis, Kogkalidis, Konstantinos, Jean-Philippe Bernardy +3 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Natural Language Processing Techniques #Topic Modeling
- Robust Simulation-Based Inference under Missing Data via Neural Processes
2025/03/03 by Y. Verma, Ayush Bharti, Verma, Yogesh +3 · 2 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Neural Networks and Applications #Machine Learning and Algorithms
- Diffusion Twigs with Loop Guidance for Conditional Graph Generation
2024/10/31 by Giangiacomo Mercatali, Yogesh Kumar Verma, Mercatali, Giangiacomo +5 · 1 citation
Computer Science · Engineering · #Advanced Materials and Mechanics #FOS: Computer and information sciences #Interactive and Immersive Displays #Machine Learning (cs.LG) #Modular Robots and Swarm Intelligence
- Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
2025/02/09 by Rafał Karczewski, Markus Heinonen, Karczewski, Rafał +3 · 2 citations
Computer Science · #Advanced Data Storage Technologies #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Peer-to-Peer Network Technologies
- Decafs: Disentangled Conditional adversarial Flows
2026/07/21 by Anirudh jain, Sakshi Varshney, Samuel Kaski +1
#cs.LG