Picture for Xiaotian Gao

Xiaotian Gao

NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition

Feb 20, 2023
Figure 1 for NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition
Figure 2 for NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition
Figure 3 for NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition
Figure 4 for NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition
Viaarxiv icon

Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization

Add code
Aug 25, 2022
Figure 1 for Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Figure 2 for Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Figure 3 for Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Figure 4 for Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Viaarxiv icon

LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data

Jun 19, 2022
Figure 1 for LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data
Figure 2 for LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data
Figure 3 for LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data
Figure 4 for LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data
Viaarxiv icon

Learning Physics-Informed Neural Networks without Stacked Back-propagation

Add code
Feb 18, 2022
Figure 1 for Learning Physics-Informed Neural Networks without Stacked Back-propagation
Figure 2 for Learning Physics-Informed Neural Networks without Stacked Back-propagation
Figure 3 for Learning Physics-Informed Neural Networks without Stacked Back-propagation
Figure 4 for Learning Physics-Informed Neural Networks without Stacked Back-propagation
Viaarxiv icon

SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation

Add code
Feb 14, 2022
Figure 1 for SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Figure 2 for SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Figure 3 for SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Figure 4 for SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Viaarxiv icon

AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing

Add code
Aug 06, 2021
Figure 1 for AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
Figure 2 for AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
Figure 3 for AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
Figure 4 for AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
Viaarxiv icon

OpEvo: An Evolutionary Method for Tensor Operator Optimization

Add code
Jun 10, 2020
Figure 1 for OpEvo: An Evolutionary Method for Tensor Operator Optimization
Figure 2 for OpEvo: An Evolutionary Method for Tensor Operator Optimization
Figure 3 for OpEvo: An Evolutionary Method for Tensor Operator Optimization
Figure 4 for OpEvo: An Evolutionary Method for Tensor Operator Optimization
Viaarxiv icon