Michael S. Albergo

1. Building Normalizing Flows with Stochastic Interpolants
   2022/09/30 by Michael S. Albergo, Albergo, Michael S., Eric Vanden-Eijnden +2 · 1 voice · 191 citations
   Computer Science · Medicine · Physics and Astronomy · #Advanced Neuroimaging Techniques and Applications #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #cs.LG #stat.ML
2. Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
   2023/03/15 by Michael S. Albergo, Nicholas M. Boffi, Albergo, Michael S. +3 · 182 citations
   Computer Science · Economics, Econometrics and Finance · Mathematics · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Probability (math.PR) #Statistical Methods and Bayesian Inference #Stochastic processes and financial applications
3. SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
   2024/01/16 by Nanye Ma, Ma, Nanye, Michael S. Albergo +8 · 157 citations
   Computer Science · Physics and Astronomy · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Music and Audio Processing
4. Stochastic interpolants with data-dependent couplings
   2023/10/05 by Michael S. Albergo, Albergo, Michael S., Nicholas M. Boffi +6 · 25 citations
   Computer Science · Biochemistry, Genetics and Molecular Biology · #Generative Adversarial Networks and Image Synthesis #Cell Image Analysis Techniques #Computer Graphics and Visualization Techniques
5. Flow map matching with stochastic interpolants: A mathematical framework for consistency models
   2024/06/11 by Nicholas M. Boffi, Michael S. Albergo, Boffi, Nicholas M. +3 · 22 citations
   Engineering · Computer Science · #Traffic Prediction and Management Techniques #Time Series Analysis and Forecasting
6. How to build a consistency model: Learning flow maps via self-distillation
   2025/05/24 by Nicholas M. Boffi, Boffi, Nicholas M., Michael S. Albergo +4 · 2 voices · 26 citations
   Computer Science · #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics #cs.CV #cs.LG
7. Aspects of scaling and scalability for flow-based sampling of lattice QCD
   2022/11/14 by Ryan Abbott, Abbott, Ryan, Michael S. Albergo +23 · 11 citations
   Decision Sciences · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Lattice (hep-lat) #Machine Learning (cs.LG) #Scientific Computing and Data Management #Statistical Mechanics (cond-mat.stat-mech) #Theoretical and Computational Physics
8. Normalizing flows for lattice gauge theory in arbitrary space-time dimension
   2023/05/03 by Ryan Abbott, Abbott, Ryan, Michael S. Albergo +25 · 7 citations
   Physics and Astronomy · Mathematics · #Particle physics theoretical and experimental studies #Probability and Statistical Research #Quantum Chromodynamics and Particle Interactions
9. LEAPS: A discrete neural sampler via locally equivariant networks
   2025/02/15 by Peter Holderrieth, Holderrieth, Peter, Michael S. Albergo +3 · 2 voices · 10 citations
   Computer Science · #Neural Networks and Applications #Target Tracking and Data Fusion in Sensor Networks
10. Sampling QCD field configurations with gauge-equivariant flow models
    2022/08/07 by Ryan Abbott, Abbott, Ryan, Michael S. Albergo +25 · 3 citations
    Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #Data Analysis with R #FOS: Physical sciences #High Energy Physics - Lattice (hep-lat) #Particle physics theoretical and experimental studies
11. Multimarginal generative modeling with stochastic interpolants
    2023/10/05 by Michael S. Albergo, Albergo, Michael S., Nicholas M. Boffi +5 · 4 citations
    Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Generative Adversarial Networks and Image Synthesis
12. Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo
    2025/02/10 by Lee, Cheuk Kit, Paul Jeha, Jes Frellsen +8 · 7 citations
    Mathematics · #Gas Dynamics and Kinetic Theory
13. Any-Order Flexible Length Masked Diffusion
    2025/08/31 by J.M. Kim, Kim, Jaeyeon, Lee Cheuk-Kit +13 · 12 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning in Healthcare
14. Learning to Sample Better
    2023/10/17 by Michael S. Albergo, Eric Vanden‐Eijnden, Albergo, Michael S. +1 · 1 citation
    Computer Science · #Cellular Automata and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
15. Multiscale Normalizing Flows for Gauge Theories
    2024/04/16 by Ryan Abbott, Abbott, Ryan, Michael S. Albergo +13 · 1 citation
    Computer Science · Engineering · #Advanced Mathematical Modeling in Engineering #Advanced Numerical Analysis Techniques #FOS: Physical sciences #High Energy Physics - Lattice (hep-lat)