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OptQuant: Distributed training of neural networks with optimized quantization mechanisms.

, , , , and . Neurocomputing, (2019)

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Invertible Rescaling Network and Its Extensions., , , , and . Int. J. Comput. Vis., 131 (1): 134-159 (2023)Predicting the protein-ligand affinity from molecular dynamics trajectories., , , , , , , , , and 1 other author(s). CoRR, (2022)One Transformer Can Understand Both 2D & 3D Molecular Data., , , , , , and . CoRR, (2022)A Dendritic Neuron Model with Nonlinearity Validation on Istanbul Stock and Taiwan Futures Exchange Indexes Prediction., , , , and . CCIS, page 242-246. IEEE, (2018)Invertible Image Rescaling., , , , , , , , and . ECCV (1), volume 12346 of Lecture Notes in Computer Science, page 126-144. Springer, (2020)Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding., , , , , , , , and . NeurIPS, page 22795-22807. (2021)OptQuant: Distributed training of neural networks with optimized quantization mechanisms., , , , and . Neurocomputing, (2019)MC-BERT: Efficient Language Pre-Training via a Meta Controller., , , , , , , and . CoRR, (2020)Do Transformers Really Perform Bad for Graph Representation?, , , , , , , and . CoRR, (2021)M-OFDFT: Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning., , , , , , , , and . CoRR, (2023)