training acceleration

MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization ICLR 2023 NerfAcc: Efficient Sampling Accelerates NeRFs ICCV 2023 Network Expansion for Practical Training Acceleration CVPR 2023 Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models NeurIPS 2023 Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training AAAI 2023 RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations ICML 2023 SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing ICLR 2023 SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow ICCV 2023 Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations NeurIPS 2022 Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt ICML 2022 Distribution Adaptive INT8 Quantization for Training CNNs AAAI 2021 A Multigrid Method for Efficiently Training Video Models CVPR 2020 ReSprop: Reuse Sparsified Backpropagation CVPR 2020 Sparse Weight Activation Training NeurIPS 2020 AutoAssist: A Framework to Accelerate Training of Deep Neural Networks NeurIPS 2019 Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks NeurIPS 2019 Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation ACL 2018 Training Deep Models Faster with Robust, Approximate Importance Sampling NeurIPS 2018