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Mandt, Stephan

  1. Advances in Variational Inference
    2017/11/15 by Cheng Zhang, Judith Bütepage, Zhang, Cheng +5 · 27 citations
    Computer Science · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  2. Lossy Image Compression with Conditional Diffusion Models
    2022/09/14 by Ruihan Yang, Stephan Mandt, Yang, Ruihan +1 · 1 voice · 26 citations
    Computer Science · #eess.IV #cs.CV #cs.LG #stat.ML
  3. GP-VAE: Deep Probabilistic Time Series Imputation
    2019/07/09 by Vincent Fortuin, Dmitry Baranchuk, Fortuin, Vincent +5 · 16 citations
    Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
  4. One Diffusion to Generate Them All
    2024/11/25 by Duong H. Le, Le, Duong H., Tuan Pham +13 · 1 voice · 16 citations
    #cs.CV #cs.AI
  5. How Good is the Bayes Posterior in Deep Neural Networks Really?
    2020/02/06 by Florian Wenzel, Kevin A. Roth, Wenzel, Florian +17 · 15 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning #Machine Learning and Algorithms
  6. Diffusion Probabilistic Modeling for Video Generation
    2022/03/16 by Yang, Ruihan, Srivastava, Prakhar, Mandt, Stephan · 15 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. Disentangled Sequential Autoencoder
    2018/03/08 by Yingzhen Li, Stephan Mandt, Li, Yingzhen +1 · 10 citations
    Computer Science · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Music Technology and Sound Studies #Music and Audio Processing
  8. Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
    2024/02/01 by Theodore Papamarkou, Maria Skoularidou, Papamarkou, Theodore +47 · 1 voice · 11 citations
    #cs.LG #stat.ML
  9. Dynamic Word Embeddings
    2017/02/27 by Bamler, Robert, Mandt, Stephan · 5 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  10. Iterative Amortized Inference
    2018/07/24 by Marino, Joseph, Yue, Yisong, Mandt, Stephan · 4 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  11. Improving Inference for Neural Image Compression
    2020/06/07 by Yibo Yang, Yang, Yibo, Robert Bamler +3 · 4 citations
    Computer Science · Physics and Astronomy · #Advanced Image Processing Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #Generative Adversarial Networks and Image Synthesis #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #electronic engineering #information engineering
  12. Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning
    2020/12/15 by Aodong Li, Alex Boyd, Li, Aodong +5 · 4 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  13. Exponential Family Embeddings
    2016/08/02 by Maja Rudolph, Rudolph, Maja R., Francisco J. R. Ruiz +5 · 3 citations
    Social Sciences · #FOS: Computer and information sciences #Family Dynamics and Relationships #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  14. Heavy-Tailed Diffusion Models
    2024/10/18 by Kushagra Pandey, Jaideep Pathak, Pandey, Kushagra +11 · 9 citations
    Computer Science · #Advanced Mathematical Modeling in Engineering #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  15. On the Challenges and Opportunities in Generative AI
    2024/02/28 by Laura Manduchi, Manduchi, Laura, Meister, Clara +48 · 6 citations
    Computer Science · #AI-based Problem Solving and Planning #Cognitive Computing and Networks #Evolutionary Algorithms and Applications
  16. The k-tied Normal Distribution: A Compact Parameterization of Gaussian\n Mean Field Posteriors in Bayesian Neural Networks
    2020/02/07 by Jakub Świątkowski, Kevin A. Roth, Swiatkowski, Jakub +17 · 5 citations
    Computer Science · #Bayesian Methods and Mixture Models #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Precipitation Downscaling with Spatiotemporal Video Diffusion
    2023/12/11 by Prakhar Srivastava, Srivastava, Prakhar, Ruihan Yang +11 · 5 citations
    Earth and Planetary Sciences · Environmental Science · #Cryospheric studies and observations #Climate variability and models #Meteorological Phenomena and Simulations
  18. ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
    2023/06/14 by Sungduk Yu, Yu, Sungduk, Z W Hu +91 · 5 citations
    Earth and Planetary Sciences · Physics and Astronomy · Environmental Science · #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #Hydrological Forecasting Using AI
  19. Lossless Compression with Probabilistic Circuits
    2021/11/23 by Anji Liu, Liu, Anji, Stephan Mandt +3 · 3 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis #Algorithms and Data Compression #Numerical Methods and Algorithms
  20. Active Mini-Batch Sampling using Repulsive Point Processes
    2018/04/08 by Cheng Zhang, Zhang, Cheng, Cengiz Öztireli +5 · 2 citations
    Engineering · Computer Science · Mathematics · #3D Shape Modeling and Analysis #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods
  21. Computationally-Efficient Neural Image Compression with Shallow Decoders
    2023/04/13 by Yang, Yibo, Mandt, Stephan · 3 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #electronic engineering #information engineering
  22. Hydra: Preserving Ensemble Diversity for Model Distillation
    2020/01/14 by Tran, Linh, Veeling, Bastiaan S., Roth, Kevin +7 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  23. Fast Samplers for Inverse Problems in Iterative Refinement Models
    2024/05/27 by Pandey, Kushagra, Yang, Ruihan, Mandt, Stephan · 5 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  24. Scalable Gaussian Process Variational Autoencoders
    2020/10/26 by Jazbec, Metod, Ashman, Matthew, Fortuin, Vincent +3 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  25. Transferring climate change physical knowledge
    2023/09/26 by Immorlano, Francesco, Eyring, Veronika, de Gouville, Thomas le Monnier +5 · 3 citations
    #Artificial Intelligence (cs.AI) #Atmospheric and Oceanic Physics (physics.ao-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG)
  26. Deep Anomaly Detection on Tennessee Eastman Process Data
    2023/03/10 by Hartung, Fabian, Franks, Billy Joe, Michels, Tobias +15 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  27. An Introduction to Neural Data Compression
    2022/02/14 by Yang, Yibo, Mandt, Stephan, Theis, Lucas · 2 citations
    #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Information Theory (cs.IT) #Machine Learning (cs.LG) #electronic engineering #information engineering
  28. Detecting Anomalies within Time Series using Local Neural Transformations
    2022/02/08 by Schneider, Tim, Qiu, Chen, Kloft, Marius +4 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  29. Smoothed Gradients for Stochastic Variational Inference
    2014/06/13 by Mandt, Stephan, Blei, David · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  30. Variational Control for Guidance in Diffusion Models
    2025/02/06 by Pandey, Kushagra, Sofian, Farrin Marouf, Draxler, Felix +2 · 5 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  31. Deep Generative Video Compression
    2018/10/05 by Han, Jun, Lombardo, Salvator, Schroers, Christopher +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #electronic engineering #information engineering
  32. Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
    2023/10/29 by Yang, Yibo, Eckstein, Stephan, Nutz, Marcel +1 · 2 citations
    #Applications (stat.AP) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  33. Unity by Diversity: Improved Representation Learning in Multimodal VAEs
    2024/03/08 by Thomas M. Sutter, Sutter, Thomas M., Yang Meng +10 · 3 citations
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multi-Agent Systems and Negotiation #Speech and dialogue systems
  34. Early-Exit Neural Networks with Nested Prediction Sets
    2023/11/10 by Jazbec, Metod, Forré, Patrick, Mandt, Stephan +2 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  35. User-Dependent Neural Sequence Models for Continuous-Time Event Data
    2020/11/06 by Alex Boyd, Robert Bamler, Boyd, Alex +5 · 1 citation
    Computer Science · Health Professions · Social Sciences · #FOS: Computer and information sciences #Human Mobility and Location-Based Analysis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Older Adults Driving Studies
  36. A Complete Recipe for Diffusion Generative Models
    2023/03/03 by Pandey, Kushagra, Mandt, Stephan · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  37. Predictive Querying for Autoregressive Neural Sequence Models
    2022/10/12 by Boyd, Alex, Showalter, Sam, Mandt, Stephan +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  38. Zero-Shot Anomaly Detection via Batch Normalization
    2023/02/15 by Aodong Li, Chen Qiu, Li, Aodong +9 · 1 citation
    Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Domain Adaptation and Few-Shot Learning
  39. Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes
    2023/02/09 by Tran, Ba-Hien, Shahbaba, Babak, Mandt, Stephan +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  40. Understanding Pathologies of Deep Heteroskedastic Regression
    2023/06/29 by Wong-Toi, Eliot, Boyd, Alex, Fortuin, Vincent +1 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  41. Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis
    2025/04/02 by Mithun, Niluthpol Chowdhury, Pham, Tuan, Wang, Qiao +6 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  42. Generative Uncertainty in Diffusion Models
    2025/02/28 by Jazbec, Metod, Wong-Toi, Eliot, Xia, Guoxuan +3 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  43. Progressive Compression with Universally Quantized Diffusion Models
    2024/12/14 by Yibo Yang, Justus C. Will, Yang, Yibo +3 · 1 citation
    Computer Science · #Advanced Data Compression Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  44. A machine-learned expression for the excess Gibbs energy
    2025/09/08 by Hoffmann, Marco, Specht, Thomas, Göttl, Quirin +4 · 1 citation
    #Computational Engineering #FOS: Computer and information sciences #Finance #Machine Learning (cs.LG) #and Science (cs.CE)
  45. SetPINNs: Set-based Physics-informed Neural Networks
    2024/09/30 by Mayank Nagda, Nagda, Mayank, Phil Ostheimer +12 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications