Showing papers from Skoltech Show all papers
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Convex Compositional Energy Minimization uses input-convex factor networks and convex relaxation to enable scalable deterministic compositional reasoning that transfers to larger instances without retraining.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Benchmarking reveals existing continuous Gromov-Wasserstein solvers fail across scenarios, and a new discrete-independent method partially fixes these issues.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Standard losses and biased activations induce negative weight drift that drives early training dynamics and extreme sparsity across architectures, with squared activations sharply improving accuracy until a cliff near 70% sparsity unless clipping controls intermediate spikes.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 1 on Hugging Face · Code ★ 1
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Midpoint Generative Models define a midpoint divergence from flow matching symmetry to train one-step generators with competitive results.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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