Jiahao Su

According to our database1, Jiahao Su authored at least 17 papers between 2018 and 2024.

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Bibliography

2024
conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks.
CoRR, 2024

2023
End-to-end Rain Streak Removal with RAW Images.
CoRR, 2023

LEMON: Lossless model expansion.
CoRR, 2023

Reviving Shift Equivariance in Vision Transformers.
CoRR, 2023

2022
Spectral Methods for Neural Network Designs.
PhD thesis, 2022

Compact Neural Architecture Designs by Tensor Representations.
Frontiers Artif. Intell., 2022

Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework.
Proceedings of the International Conference on Machine Learning, 2022

Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders.
CoRR, 2021

Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework.
CoRR, 2021

2020
Convolutional Tensor-Train LSTM for Spatio-temporal Learning.
CoRR, 2020

Convolutional Tensor-Train LSTM for Spatio-Temporal Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

ARMA Nets: Expanding Receptive Field for Dense Prediction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sampling-Free Learning of Bayesian Quantized Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Understanding Generalization in Deep Learning via Tensor Methods.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018
Tensorized Spectrum Preserving Compression for Neural Networks.
CoRR, 2018


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