TabPFN is a Prior-Data Fitted Network that approximates Bayesian inference for small tabular classification by training a Transformer once on synthetic data drawn from a causal prior, then solves new tasks in a single forward pass without further updates.
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DiffPhD delivers a unified differentiable projective dynamics solver for heterogeneous hyperelastic elastodynamics with contact that achieves up to 10x speedup and stable convergence on 100x stiffness contrasts while preserving strict gradient accuracy.
Schema-1 is the first Data Language Model that natively understands raw tabular data and outperforms gradient-boosted ensembles, AutoML, and prior tabular foundation models on row-level prediction and imputation tasks.
Pioneer Agent automates the full lifecycle of adapting and continually improving small language models via diagnosis-driven data synthesis and regression-constrained retraining, delivering gains of 1.6-83.8 points on benchmarks and large lifts in production-style tasks.
Betti curves from persistent homology of large-scale structure provide complementary cosmological constraints on ns, sigma8, and Om, with tighter bounds when analyzed jointly with the power spectrum.
citing papers explorer
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TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
TabPFN is a Prior-Data Fitted Network that approximates Bayesian inference for small tabular classification by training a Transformer once on synthetic data drawn from a causal prior, then solves new tasks in a single forward pass without further updates.
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DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration
DiffPhD delivers a unified differentiable projective dynamics solver for heterogeneous hyperelastic elastodynamics with contact that achieves up to 10x speedup and stable convergence on 100x stiffness contrasts while preserving strict gradient accuracy.
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Data Language Models: A New Foundation Model Class for Tabular Data
Schema-1 is the first Data Language Model that natively understands raw tabular data and outperforms gradient-boosted ensembles, AutoML, and prior tabular foundation models on row-level prediction and imputation tasks.
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Pioneer Agent: Continual Improvement of Small Language Models in Production
Pioneer Agent automates the full lifecycle of adapting and continually improving small language models via diagnosis-driven data synthesis and regression-constrained retraining, delivering gains of 1.6-83.8 points on benchmarks and large lifts in production-style tasks.
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Counting voids and filaments: Betti Curves as a Powerful Probe for Cosmology
Betti curves from persistent homology of large-scale structure provide complementary cosmological constraints on ns, sigma8, and Om, with tighter bounds when analyzed jointly with the power spectrum.