Stephan Mandt
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
49
Venues
12
Active years
2016–2025
Best venue rank
A*
Where they publish
Papers
49 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | One Diffusion to Generate Them All. | Duong H. Le, Tuan Pham, Sangho Lee, Christopher Clark, Aniruddha Kembhavi, Stephan Mandt, Ranjay Krishna, Jiasen Lu |
| 2025 | ICCV | GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation. | Tuan Pham, Thanh-Tung Le, Xiaohui Xie, Stephan Mandt |
| 2025 | ICLR | Heavy-Tailed Diffusion Models. | Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael S. Pritchard, Arash Vahdat, Morteza Mardani |
| 2025 | ICLR | AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data. | Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom |
| 2025 | ICLR | Progressive Compression with Universally Quantized Diffusion Models. | Yibo Yang, Justus C. Will, Stephan Mandt |
| 2025 | ICML | Variational Control for Guidance in Diffusion Models. | Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler, Theofanis Karaletsos, Stephan Mandt |
| 2025 | UAI | Generative Uncertainty in Diffusion Models. | Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt |
| 2024 | ICLR | Efficient Integrators for Diffusion Generative Models. | Kushagra Pandey, Maja Rudolph, Stephan Mandt |
| 2024 | ICML | Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. | Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jos Miguel Hernndez-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rgamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang |
| 2024 | ICML | Neural NeRF Compression. | Tuan Pham, Stephan Mandt |
| 2024 | UAI | Early-Exit Neural Networks with Nested Prediction Sets. | Metod Jazbec, Patrick Forr, Stephan Mandt, Dan Zhang, Eric T. Nalisnick |
| 2024 | UAI | Understanding Pathologies of Deep Heteroskedastic Regression. | Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt |
| 2023 | AISTATS | Probabilistic Querying of Continuous-Time Event Sequences. | Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth |
| 2023 | ICCV | A Complete Recipe for Diffusion Generative Models. | Kushagra Pandey, Stephan Mandt |
| 2023 | ICCV | Computationally-Efficient Neural Image Compression with Shallow Decoders. | Yibo Yang, Stephan Mandt |
| 2023 | ICML | Deep Anomaly Detection under Labeling Budget Constraints. | Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph |
| 2023 | ICML | Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes. | Ba-Hien Tran, Babak Shahbaba, Stephan Mandt, Maurizio Filippone |
| 2023 | UAI | Inference for mark-censored temporal point processes. | Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth |
| 2022 | ICLR | Lossless Compression with Probabilistic Circuits. | Anji Liu, Stephan Mandt, Guy Van den Broeck |
| 2022 | ICLR | Towards Empirical Sandwich Bounds on the Rate-Distortion Function. | Yibo Yang, Stephan Mandt |
| 2022 | ICML | Structured Stochastic Gradient MCMC. | Antonios Alexos, Alex J. Boyd, Stephan Mandt |
| 2022 | ICML | Latent Outlier Exposure for Anomaly Detection with Contaminated Data. | Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt |
| 2022 | IJCAI | Raising the Bar in Graph-level Anomaly Detection. | Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph |
| 2022 | WACV | Supervised Compression for Resource-Constrained Edge Computing Systems. | Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt |
| 2021 | AISTATS | Scalable Gaussian Process Variational Autoencoders. | Metod Jazbec, Matthew Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rtsch |
| 2021 | ICLR | Hierarchical Autoregressive Modeling for Neural Video Compression. | Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt |
| 2021 | ICML | Neural Transformation Learning for Deep Anomaly Detection Beyond Images. | Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph |
| 2020 | AISTATS | GP-VAE: Deep Probabilistic Time Series Imputation. | Vincent Fortuin, Dmitry Baranchuk, Gunnar Rtsch, Stephan Mandt |
| 2020 | ICLR | Extreme Classification via Adversarial Softmax Approximation. | Robert Bamler, Stephan Mandt |
| 2020 | ICML | The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. | Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
| 2020 | ICML | How Good is the Bayes Posterior in Deep Neural Networks Really? | Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
| 2020 | ICML | Variational Bayesian Quantization. | Yibo Yang, Robert Bamler, Stephan Mandt |
| 2019 | AAAI | Active Mini-Batch Sampling Using Repulsive Point Processes. | Cheng Zhang, Cengiz ztireli, Stephan Mandt, Giampiero Salvi |
| 2019 | EMNLP | Autoregressive Text Generation Beyond Feedback Loops. | Florian Schmidt, Stephan Mandt, Thomas Hofmann |
| 2019 | ICRA | Mobile Robotic Painting of Texture. | Majed El Helou, Stephan Mandt, Andreas Krause, Paul A. Beardsley |
| 2019 | UAI | Augmenting and Tuning Knowledge Graph Embeddings. | Robert Bamler, Farnood Salehi, Stephan Mandt |
| 2018 | AISTATS | Scalable Generalized Dynamic Topic Models. | Patrick Jhnichen, Florian Wenzel, Marius Kloft, Stephan Mandt |
| 2018 | CoNLL | Continuous Word Embedding Fusion via Spectral Decomposition. | Tianfan Fu, Cheng Zhang, Stephan Mandt |
| 2018 | ICLR | Learning to Infer. | Joseph Marino, Yisong Yue, Stephan Mandt |
| 2018 | ICML | Improving Optimization in Models With Continuous Symmetry Breaking. | Robert Bamler, Stephan Mandt |
| 2018 | ICML | Quasi-Monte Carlo Variational Inference. | Alexander Buchholz, Florian Wenzel, Stephan Mandt |
| 2018 | ICML | Disentangled Sequential Autoencoder. | Yingzhen Li, Stephan Mandt |
| 2018 | ICML | Iterative Amortized Inference. | Joseph Marino, Yisong Yue, Stephan Mandt |
| 2017 | CVPR | Factorized Variational Autoencoders for Modeling Audience Reactions to Movies. | Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain A. Matthews, Greg Mori |
| 2017 | ICML | Dynamic Word Embeddings. | Robert Bamler, Stephan Mandt |
| 2017 | UAI | Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes. | Cheng Zhang, Hedvig Kjellstrm, Stephan Mandt |
| 2016 | AISTATS | Variational Tempering. | Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei |
| 2016 | ICML | A Variational Analysis of Stochastic Gradient Algorithms. | Stephan Mandt, Matthew D. Hoffman, David M. Blei |
| 2016 | UAI | Separating Sparse Signals from Correlated Noise in Binary Classification. | Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft |