Robert Bamler

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Variational Inference

Structured Domains

Arithmetic Coding

Sequential Monte Carlo

Top Venues

Publications

Andi Zhang, Tim Z. Xiao, Weiyang Liu, Robert Bamler, Damon Wischik
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector. CoRR (2024)
Tristan Cinquin, Marvin Pförtner, Vincent Fortuin, Philipp Hennig, Robert Bamler
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning. CoRR (2024)
Johannes Zenn, Robert Bamler
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution. CoRR (2024)
Johannes Zenn, Dominik Gond, Fabian Jirasek, Robert Bamler
Balancing Molecular Information and Empirical Data in the Prediction of Physico-Chemical Properties. CoRR (2024)
Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin
On the Challenges and Opportunities in Generative AI. CoRR (2024)
Tristan Cinquin, Robert Bamler
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks. CoRR (2024)
Hanqi Zhou, Robert Bamler, Charley M. Wu, Álvaro Tejero-Cantero
Predictive, scalable and interpretable knowledge tracing on structured domains. ICLR (2024)
Hanqi Zhou, Robert Bamler, Charley M. Wu, Álvaro Tejero-Cantero
Predictive, scalable and interpretable knowledge tracing on structured domains. CoRR (2024)
Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
Verbalized Machine Learning: Revisiting Machine Learning with Language Models. CoRR (2024)
Tim Z. Xiao, Weiyang Liu, Robert Bamler
A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry. CoRR (2024)
Tim Z. Xiao, Robert Bamler
Trading Information between Latents in Hierarchical Variational Autoencoders. ICLR (2023)
Tim Z. Xiao, Johannes Zenn, Robert Bamler
Upgrading VAE Training With Unlimited Data Plans Provided by Diffusion Models. CoRR (2023)
Tim Z. Xiao, Johannes Zenn, Robert Bamler
The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch. CoRR (2023)
Tim Z. Xiao, Robert Bamler
Trading Information between Latents in Hierarchical Variational Autoencoders. CoRR (2023)
Johannes Zenn, Robert Bamler
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers. CoRR (2023)
Johannes Zenn, Robert Bamler
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers. Tiny Papers @ ICLR (2023)
Robert Bamler
Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective. CoRR (2022)
Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
User-Dependent Neural Sequence Models for Continuous-Time Event Data. NeurIPS (2020)
Robert Bamler, Stephan Mandt
Extreme Classification via Adversarial Softmax Approximation. CoRR (2020)
Robert Bamler, Stephan Mandt
Extreme Classification via Adversarial Softmax Approximation. ICLR (2020)
Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
User-Dependent Neural Sequence Models for Continuous-Time Event Data. CoRR (2020)
Yibo Yang, Robert Bamler, Stephan Mandt
Variational Bayesian Quantization. ICML (2020)
Yibo Yang, Robert Bamler, Stephan Mandt
Improving Inference for Neural Image Compression. NeurIPS (2020)
Yibo Yang, Robert Bamler, Stephan Mandt
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding. CoRR (2020)
Yibo Yang, Robert Bamler, Stephan Mandt
Improving Inference for Neural Image Compression. CoRR (2020)
Robert Bamler, Stephan Mandt
A Quantum Field Theory of Representation Learning. CoRR (2019)
Robert Bamler, Farnood Salehi, Stephan Mandt
Augmenting and Tuning Knowledge Graph Embeddings. UAI (2019)
Robert Bamler, Farnood Salehi, Stephan Mandt
Augmenting and Tuning Knowledge Graph Embeddings. CoRR (2019)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory. CoRR (2019)
Robert Bamler, Stephan Mandt
Improving Optimization in Models With Continuous Symmetry Breaking. ICML (2018)
Robert Bamler, Stephan Mandt
Improving Optimization in Models With Continuous Symmetry Breaking. CoRR (2018)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Perturbative Black Box Variational Inference. CoRR (2017)
Geng Ji, Robert Bamler, Erik B. Sudderth, Stephan Mandt
Bayesian Paragraph Vectors. CoRR (2017)
Robert Bamler, Stephan Mandt
Dynamic Word Embeddings. ICML (2017)
Robert Bamler, Stephan Mandt
Dynamic Word Embeddings via Skip-Gram Filtering. CoRR (2017)
Robert Bamler, Stephan Mandt
Structured Black Box Variational Inference for Latent Time Series Models. CoRR (2017)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Perturbative Black Box Variational Inference. NIPS (2017)