Patrick Forré

1. Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
   2021/02/10 by Emiel Hoogeboom, Hoogeboom, Emiel, Didrik Nielsen +7 · 79 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Music and Audio Processing #Machine Learning in Healthcare
2. Learning Robust Representations via Multi-View Information Bottleneck
   2020/02/17 by Marco Federici, Federici, Marco, Anjan Dutta +7 · 20 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #Multimodal Machine Learning Applications #Advanced Neural Network Applications
3. Clifford Group Equivariant Neural Networks
   2023/05/18 by David Ruhe, Ruhe, David, J. Brandstetter +3 · 9 citations
   Medicine · Neuroscience · Physics and Astronomy · #Advanced Neuroimaging Techniques and Applications #Artificial Intelligence (cs.AI) #Brain Tumor Detection and Classification #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks
4. Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
   2021/06/10 by Maurice Weiler, Weiler, Maurice, Patrick Forré +5 · 6 citations
   Engineering · Computer Science · #3D Shape Modeling and Analysis #Advanced Numerical Analysis Techniques #Advanced Vision and Imaging
5. An Information-theoretic Approach to Distribution Shifts
   2021/06/07 by Marco Federici, Ryota Tomioka, Federici, Marco +3 · 4 citations
   Computer Science · #Data Stream Mining Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
6. Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
   2023/09/13 by Marco Orsini Federici, Patrick Forré, Federici, Marco +5 · 3 citations
   Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Information Theory (cs.IT) #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Time Series Analysis and Forecasting
7. Contrastive Neural Ratio Estimation for Simulation-based Inference
   2022/10/11 by B. Miller, Christoph Weniger, Miller, Benjamin Kurt +3 · 2 citations
   Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Neural Networks and Applications
8. Clifford-Steerable Convolutional Neural Networks
   2024/02/22 by Maksim Zhdanov, David Ruhe, Zhdanov, Maksim +9 · 3 citations
   Computer Science · Neuroscience · #Artificial Intelligence (cs.AI) #Brain Tumor Detection and Classification #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
9. Lie Group Decompositions for Equivariant Neural Networks
   2023/10/17 by Mircea Mironenco, Patrick Forré, Mironenco, Mircea +1 · 2 citations
   Computer Science · Engineering · #AI in cancer detection #Digital Imaging for Blood Diseases #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Medical Imaging and Analysis
10. Self-Supervised Inference in State-Space Models
    2021/07/28 by David Ruhe, Ruhe, David, Patrick Forré +1 · 1 citation
    Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
11. Information Decomposition Diagrams Applied beyond Shannon Entropy: A Generalization of Hu's Theorem
    2022/02/28 by Leon Lang, Pierre Baudot, Rick Quax +1 · 2 citations
    Computer Science · #Neural Networks and Applications