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cs.LG2026
Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
Julien Lalanne, David Picard, Lionel Boillot +3
Generative modeling provides a powerful framework for learning data distributions. These models initially relied on probabilistic methods such as Gaussian Processes (GP) for uncert…
cs.LG2025
Markov Chain Estimation with In-Context Learning
Simon Lepage, Jeremie Mary, David Picard
We investigate the capacity of transformers to learn algorithms involving their context while solely being trained using next token prediction. We set up Markov chains with random…