Simplifying Optimal Transport through Schatten-$p$ Regularization Tyler Maunu Action editor: Ju Sun https://openreview.net/forum?id=DIawkTG5VH #regularization #transport #sparse
The Diffusion Process as a Correlation Machine: Linear Denoising Insights Dana Weitzner, Mauricio Delbracio, Peyman Milanfar, Raja Giryes Action editor: Arno Solin https://openreview.net/forum?id=FGDJOc27rt #denoising #denoisers #denoiser
Mesh-Informed Neural Operator : A Transformer Generative Approach Yaozhong Shi, Zachary E Ross, Domniki Asimaki, Kamyar Azizzadenesheli Action editor: Andriy Mnih https://openreview.net/forum?id=K8qAuRfv0G #generative #mesh #functional
Improved seeding strategies for k-means and k-GMM Guillaume Carrière, Frederic Cazals Action editor: Kejun Huang https://openreview.net/forum?id=4Ut2YnekhN #seeding #clustering #randomized
Slicing the Gaussian Mixture Wasserstein Distance Moritz Piening, Robert Beinert Action editor: Makoto Yamada https://openreview.net/forum?id=yPBtJ4JPwi #wasserstein #generative #minimization
Yucen Lily Li, Daohan Lu, Polina Kirichenko, Shikai Qiu, Tim G. J. Rudner, C. Bayan Bruss, Andrew Gordon Wilson: Out-of-Distribution Detection Methods Answer the Wrong Questions https://arxiv.org/abs/2507.01831 https://arxiv.org/pdf/2507.01831 https://arxiv.org/html/2507.01831
Sloan Nietert, Ziv Goldfeld Estimation of Stochastic Optimal Transport Maps https://arxiv.org/abs/2512.09499
A Comprehensive Survey on Knowledge Distillation Amir M. Mansourian, Rozhan Ahmadi, Masoud Ghafouri et al. Action editor: Changyou Chen https://openreview.net/forum?id=3cbJzdR78B #distillation #dnns #knowledge
Survey of Video Diffusion Models: Foundations, Implementations, and Applications Yimu Wang, Xuye Liu, Wei Pang, Li Ma, Shuai Yuan, Paul Debevec, Ning Yu Action editor: Anurag Arnab https://openreview.net/forum?id=2ODDBObKjH #video #generative #visual
Open Problems in Mechanistic Interpretability Lee Sharkey, Bilal Chughtai, Joshua Batson et al. Action editor: Sarath Chandar https://openreview.net/forum?id=91H76m9Z94 #interpretability #ai #mechanistic
Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt Action editor: Shinichi Nakajima https://openreview.net/forum?id=Bt0zdsnWYc #outliers #anomaly #anomalies
Wondering how DeepSeek v3.2 rivals SOTA models (e.g., GPT5/Gemini 3 pro) while being ~30x cheaper? 🤔 Let's learn how the base model works! We'll focus on attention, the need for KV caching, and key ideas for improving attention (MQA/GQA/MLA/DSA). youtu.be/Y-o545eYjXM
Label Embedding via Low-Coherence Matrices Jianxin Zhang, Clayton Scott Action editor: Jake C. Snell https://openreview.net/forum?id=vrcWXcr4On #embedding #classification #label
🚨 OpenReview might have leaked names, but it won't leak the best hyperparameters, unfortunately! 😅 Tired of the drama? Solve your HPO problems before the ICML deadline with this new monograph by our own Luca Franceschi & Massimiliano Pontil (& colleagues). arxiv.org/abs/2410.22854
Hyperparameter Optimization in Machine Learning
Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the choice of their values ...
arxiv.org
I'm quite intrigued by possibility theory, so I must say this looks quite exciting! arxiv.org/abs/2511.21223
Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference
Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models that would otherwise be intractable. However, its formulation depends on expec...
arxiv.org
🔄 Updated Arxiv Paper Title: Modelling Global Trade with Optimal Transport Authors: Thomas Gaskin, Guven Demirel, Marie-Therese Wolfram, Andrew Duncan Read more: https://arxiv.org/abs/2409.06554
A Mixture of Exemplars Approach for Efficient Out-of-Distribution Detection with Foundation Models Evelyn Mannix, Howard Bondell Action editor: Gabriel Loaiza-Ganem https://openreview.net/forum?id=xpKqnSJtE4 #classifier #detection #classification
A Unified Approach Towards Active Learning and Out-of-Distribution Detection Sebastian Schmidt, Leonard Schenk, Leo Schwinn, Stephan Günnemann Action editor: Chicheng Zhang https://openreview.net/forum?id=HL75La10FN #detection #deep #feature
Reading group tomorrow: "How to build a consistency model: Learning flow maps via self-distillation" with Nicholas Boffi! arxiv.org/abs/2505.18825 Join us on zoom at 9am PT, 12pm ET, 6pm CET: portal.valencelabs.com/starklyspeak...
Unifying Self-Supervised Clustering and Energy-Based Models Emanuele Sansone, Robin Manhaeve Action editor: Ole Winther https://openreview.net/forum?id=NW0uKe6IZa #generative #supervised #models
Entangled Schrödinger Bridge Matching][new] Models interacting particle dynamics by entangling velocities via coupled bias forces, improving trajectory simulation for systems with evolving interactions.
Does equivariance matter at scale? Johann Brehmer, Sönke Behrends, Pim De Haan, Taco Cohen Action editor: Marcus Brubaker https://openreview.net/forum?id=wilNute8Tn #models #equivariance #equivariant
"The Principles of Diffusion Models" by Chieh-Hsin Lai, Yang Song, Dongjun Kim, Yuki Mitsufuji, Stefano Ermon. arxiv.org/abs/2510.21890 It might not be the easiest intro to diffusion models, but this monograph is an amazing deep dive into the math behind them and all the nuances
The Principles of Diffusion Models
This monograph presents the core principles that have guided the development of diffusion models, tracing their origins and showing how diverse formulations arise from shared mathematical ideas. Diffu...
arxiv.org
New paper on arXiv! And I think it's a good'un 😄 Meet the new Lattice Random Walk (LRW) discretisation for SDEs. It’s radically different from traditional methods like Euler-Maruyama (EM) in that each iteration can only move in discrete steps {-δₓ, 0, δₓ}.
Samuel Duffield, Maxwell Aifer, Denis Melanson, Zach Belateche, Patrick J. Coles Lattice Random Walk Discretisations of Stochastic Differential Equations https://arxiv.org/abs/2508.20883
Luca Ambrogioni The Information Dynamics of Generative Diffusion https://arxiv.org/abs/2508.19897
Great stuff: arxiv.org/abs/2508.18175
Amortized Sampling with Transferable Normalizing Flows
Efficient equilibrium sampling of molecular conformations remains a core challenge in computational chemistry and statistical inference. Classical approaches such as molecular dynamics or Markov chain...
arxiv.org
A random old one: "Kernels and Decision Trees" hackmd.io/@sp-monte-ca...
Sam Power@spmontecarlo.bsky.social · last yr.My memory is that I have a few mostly-written drafts waiting in the wings on HackMD, and I'll try to upload them soon. I'm also thinking about writing exercises which might be fun for me to explore, e.g. picking some topic from a list and taking <30 mins to write a personal impression / overview.
