Showing 1–16 of 16 results
/ Date/ Name
Dec 14, 2023Symmetry Breaking and Equivariant Neural NetworksJun 17, 2025Accurate and scalable exchange-correlation with deep learningNov 29, 2021Prediction of Large Magnetic Moment Materials With Graph Neural Networks and Random ForestsNov 11, 2022Equivariance with Learned Canonicalization FunctionsDec 4, 2025LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative ModelsFeb 5, 2025SymmCD: Symmetry-Preserving Crystal Generation with Diffusion ModelsNov 3, 2025Energy Loss Functions for Physical SystemsMar 27, 2025Improving Equivariant Networks with Probabilistic Symmetry BreakingMar 13, 2025On the Identifiability of Causal AbstractionsNov 15, 2022Equivariant Networks for Crystal StructuresJan 14, 2025Symmetry-Aware Generative Modeling through Learned CanonicalizationOct 2, 2023Equivariant Adaptation of Large Pretrained ModelsFeb 9, 2026Inverting Data Transformations via Diffusion SamplingSep 6, 2023Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural NetworksNov 18, 2020Gradient Starvation: A Learning Proclivity in Neural NetworksApr 28, 2026The Role of Symmetry in Optimizing Overparameterized Networks