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Please visit the current reading group webpage at https://bamler-lab.github.io/reading_group.

The list below is no longer being updated.

Reading Group @BamlerLab

MvL6: 4th floor seminar room (Thursday 1:30 pm ($\color{olive}{\textsf{General}}$) and Monday 3:00 pm ($\color{orange}{\textsf{Compression}}$))

The BamlerLab reading group ($\color{olive}{\textsf{General}}$) meets weekly on Thursdays to engage in a comprehensive exploration and interpretation of scholarly works. The material to be examined can be accessed at the following link: https://github.com/bamler-lab/reading-group. Your participation in the group is cordially invited, and should you choose to attend, please feel free to join in the discussion.

Additionally, we're thrilled to introduce a new reading group exclusively centered on compression topics ($\color{orange}{\textsf{Compression}}$). This exciting venture convenes every Monday. It promises to be an engaging forum for those passionate about compression algorithms and techniques.

We thank ChatGPT for writing this description.

2024

Date	Moderator	Title of Paper & Link to Paper	talks.tue	comment	reading group
2024/09/12	all participants	Experiences and Trends at ICML 2024	N/A		$\color{olive}{\textsf{General}}$
2024/08/08	Robert Bamler	Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution	talks.tue		$\color{olive}{\textsf{General}}$
2024/07/29	all participants	Neural Discrete Representation Learning	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/07/15	all participants	The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/07/11	Tristan Cinquin	Randomized Algorithms for Matrix Computations (Chapters 3-5)	talks.tue		$\color{olive}{\textsf{General}}$
2024/07/04	Robert Bamler	Randomized Algorithms for Matrix Computations (Chapters 1-3)	talks.tue		$\color{olive}{\textsf{General}}$
2024/06/24	all participants	Distribution Compression in Near-linear Time	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/06/17	all participants	Estimating the Rate-Distortion Function by Wasserstein Gradient Descent	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/05/13	all participants	Lossy Image Compression with Conditional Diffusion Models	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/05/06	all participants	Out-of-Distribution Detection using Maximum Entropy Coding	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/04/29	all participants	On universal quantization	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/04/22	all participants	Universal Deep Neural Network Compression	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/04/11	Alexander Conzelmann	Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning	talks.tue		$\color{olive}{\textsf{General}}$
2024/04/08	all participants	Lossy Compression with Gaussian Diffusion	talks.tue	Part 2/2	$\color{orange}{\textsf{Compression}}$
2024/04/04	Tim Xiao	LoRA: Low-Rank Adaptation of Large Language Models	talks.tue		$\color{olive}{\textsf{General}}$
2024/03/21	Tristan Cinquin	Bayesian Model Selection, the Marginal Likelihood, and Generalization	talks.tue		$\color{olive}{\textsf{General}}$
2024/03/18	all participants	Lossy Compression with Gaussian Diffusion	talks.tue	Part 1/2	$\color{orange}{\textsf{Compression}}$
2024/03/14	Johannes Zenn	Diffusion Schrödinger Bridge Matching	talks.tue	Part 2/2	$\color{olive}{\textsf{General}}$
2024/03/11	all participants	Language Modeling is Compression	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/03/07	Johannes Zenn	Diffusion Schrödinger Bridge Matching	talks.tue	Part 1/2	$\color{olive}{\textsf{General}}$
2024/03/04	all participants	Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables	talks.tue		$\color{orange}{\textsf{Compression}}$
2024/02/29	Alexander Conzelmann	Learning Generative Models with Sinkhorn Divergences	talks.tue		$\color{olive}{\textsf{General}}$
2024/02/26	all participants	Wasserstein Distortion: Unifying Fidelity and Realism	N/A		$\color{orange}{\textsf{Compression}}$
2024/02/19	all participants	Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding	N/A		$\color{orange}{\textsf{Compression}}$
2024/02/15	Robert Bamler	Introduction to Optimal Transport	N/A		$\color{olive}{\textsf{General}}$
2024/02/08	Alexander Conzelmann	Low-Precision Stochastic Gradient Langevin Dynamics	N/A		$\color{olive}{\textsf{General}}$
2024/01/11	Tim Xiao & Johannes Zenn	Experiences and Trends at NeurIPS 2023	N/A		$\color{olive}{\textsf{General}}$

2023

Date	Moderator	Title of Paper & Link to Paper	talks.tue	comment	reading group
2023/12/07	Robert Bamler	Show and Tell Session	talks.tue	Show and Tell Session	$\color{olive}{\textsf{General}}$
2023/11/30	Lenard Rommel	Finite Volume Neural Networks for Simple Vortex Problems	talks.tue	Bachelor's Thesis Presentation	$\color{olive}{\textsf{General}}$
2023/11/23	Johannes Zenn	More Faithful Variational Inference via the Initial Distribution of Differentiable Annealed Importance Sampling	talks.tue		$\color{olive}{\textsf{General}}$
2023/10/26	Tristan Cinquin	Regularized KL-Divergence for Well-Defined Function Space Variational Inference in BNNs	talks.tue		$\color{olive}{\textsf{General}}$
2023/09/07	Alexander Ludwig	Neural Data Compression for Magnetic Resonance Imaging	talks.tue	Bachelor's Thesis Presentation	$\color{olive}{\textsf{General}}$
2023/08/31	Nicolò Zottino	Probabilistic Circuits	talks.tue	Talk	$\color{olive}{\textsf{General}}$
2023/08/17	Robert Bamler	Algorithms for the Communication of Samples	talks.tue		$\color{olive}{\textsf{General}}$
2023/08/10	Robert Bamler	Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow	talks.tue		$\color{olive}{\textsf{General}}$
2023/07/20	Tim Xiao	DreamFusion: Text-to-3D using 2D Diffusion	talks.tue		$\color{olive}{\textsf{General}}$
2023/07/06	Alexander Conzelmann	From data to functa: Your data point is a function and you can treat it like one	talks.tue		$\color{olive}{\textsf{General}}$
2023/05/25	Johannes Zenn	Diffusion Probabilistic Fields	talks.tue		$\color{olive}{\textsf{General}}$
2023/04/27	Tim Xiao Johannes Zenn	Trading Information between Latents in Hierarchical Variational Autoencoders Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers	talks.tue talks.tue	Poster Presentation	$\color{olive}{\textsf{General}}$
2023/04/12	Robert Bamler	Finite Volume Neural Network: Modeling Subsurface Contaminant Transport	talks.tue		$\color{olive}{\textsf{General}}$
2023/03/30	Nicolò Zottino	Peer-to-Peer Variational Federated Learning Over Arbitrary Graphs	talks.tue		$\color{olive}{\textsf{General}}$
2023/03/16	Johannes Zenn	Langevin Diffusion Variational Inference	talks.tue		$\color{olive}{\textsf{General}}$
2023/03/02	Tim Xiao	Git Re-Basin: Merging Models modulo Permutation Symmetries	talks.tue		$\color{olive}{\textsf{General}}$
2023/02/23	Tristan Cinquin	Understanding Variational Inference in Function-Space	talks.tue		$\color{olive}{\textsf{General}}$
2023/02/09	Alexander Conzelmann	Diffusion Probabilistic Modeling for Video Generation	N/A		$\color{olive}{\textsf{General}}$