JanusPipe introduces SymFold and WaveK to enable efficient 3D-parallel training for conservative MLIPs, reporting 1.51x and 1.45x average throughput gains over 1F1B and Hanayo baselines on 32 GPUs.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Introduces TEDBench benchmark and MiAE self-supervised framework that outperforms baselines for large-scale protein fold classification.
DFTB models for cerium allotropes were created that accurately predict band structures and energetic ordering by globally optimizing confining potentials to fit minimal DFT data and extract a many-body repulsive term.
citing papers explorer
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JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
JanusPipe introduces SymFold and WaveK to enable efficient 3D-parallel training for conservative MLIPs, reporting 1.51x and 1.45x average throughput gains over 1F1B and Hanayo baselines on 32 GPUs.
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Protein Fold Classification at Scale: Benchmarking and Pretraining
Introduces TEDBench benchmark and MiAE self-supervised framework that outperforms baselines for large-scale protein fold classification.
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Determination of Density Functional Tight Binding Models for Cerium Allotropes
DFTB models for cerium allotropes were created that accurately predict band structures and energetic ordering by globally optimizing confining potentials to fit minimal DFT data and extract a many-body repulsive term.