Kachman, Tal
- Gradients are Not All You Need
2021/11/10 by Luke Metz, C. Daniel Freeman, Metz, Luke +5 · 2 voices · 9 citations
#cs.LG #stat.ML
- Gotta Go Fast When Generating Data with Score-Based Models
2021/05/28 by Alexia Jolicoeur‐Martineau, Jolicoeur-Martineau, Alexia, Ke Li +7 · 12 citations
Computer Science · Medicine · Physics and Astronomy · #Advanced Neuroimaging Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Optimization and Control (math.OC)
- Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
2023/09/18 by Alexia Jolicoeur-Martineau, Jolicoeur-Martineau, Alexia, Kilian Fatras +3 · 2 voices · 4 citations
#cs.LG
- Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation
2022/10/02 by Yannick Hogewind, Thiago D. Simão, Hogewind, Yannick +5 · 3 citations
Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #Reinforcement Learning in Robotics
- Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels
2018/05/30 by Vadim Ratner, Ratner, Vadim, Yoel Shoshan +3 · 1 citation
Computer Science · #AI in cancer detection #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Text and Document Classification Technologies
- Diffusion models with location-scale noise
2023/04/12 by Alexia Jolicoeur‐Martineau, Kilian Fatras, Jolicoeur-Martineau, Alexia +5 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Neural Networks and Applications #Numerical Analysis (math.NA)
- Charting the Topography of the Neural Network Landscape with Thermal-Like Noise
2023/04/03 by Jules, Theo, Brener, Gal, Kachman, Tal +2 · 1 citation
#FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Statistical Mechanics (cond-mat.stat-mech)
- Explainability Techniques for Chemical Language Models
2023/05/25 by Stefan Hödl, Hödl, Stefan, William H. Robinson +7 · 1 citation
Computer Science · Materials Science · #Artificial Intelligence (cs.AI) #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Quantitative Methods (q-bio.QM)
- Modelling Chemical Reaction Networks using Neural Ordinary Differential Equations
2025/02/11 by Anna C. M. Thöni, William E. Robinson, Thöni, Anna C. M. +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Materials Science · Physics and Astronomy · #FOS: Biological sciences #FOS: Computer and information sciences #Gene Regulatory Network Analysis #Machine Learning (cs.LG) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Molecular Networks (q-bio.MN)