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Variational Methods for Simulation Based Inference
A new framework for likelihood-free inference, i.e. the task of using probabilistic / Bayesian Methods in the absence of tractable …
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Improving cooperative game theory-based data valuation via data utility learning
Data valuation is typically limited by the exponential complexity of retraining for each possible subset of training points. This paper …
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Progressive Distillation for Fast Sampling of Diffusion Models
The generation process of diffusion models can be sped up by using a slow teacher model for training a faster student - the latter …
Blog
Our take on ICLR 2022 - Part 1
ICLR is one of the most important and prestigious conferences in the ML community. It spans all ML topics, from embeddings to Graph neural …
Pill
Comparing Distributions by Measuring Differences that Affect Decision Making
A new family of divergences for distributions is introduced, generalizing KL and others, together with an efficient estimator for it. A …
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Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
In this rather technical paper, a new dynamics is proposed for the sampling of diffusion models. Instead of sampling the de-noised image …
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