🏢 University of Stuttgart
Constrained Sampling with Primal-Dual Langevin Monte Carlo
·2374 words·12 mins·
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AI Theory
Optimization
🏢 University of Stuttgart
Constrained sampling made easy! Primal-Dual Langevin Monte Carlo efficiently samples from complex probability distributions while satisfying statistical constraints.
Consistency Models for Scalable and Fast Simulation-Based Inference
·3014 words·15 mins·
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Machine Learning
Deep Learning
🏢 University of Stuttgart
CMPE: a new conditional sampler for SBI, achieves fast few-shot inference with an unconstrained architecture, outperforming current state-of-the-art algorithms on various benchmarks.