Tianyang Hu

Orcid: 0009-0006-8814-2215

According to our database1, Tianyang Hu authored at least 28 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Improving the Computerized Ionospheric Tomography Performance Through a Neural Network-Based Initial IED Prediction Model.
IEEE Trans. Geosci. Remote. Sens., 2024

Label-Driven Graph Convolutional Network for Multilabel Remote Sensing Image Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

Accelerating Diffusion Sampling with Optimized Time Steps.
CoRR, 2024

Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion.
CoRR, 2024

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling.
CoRR, 2024

On the Expressive Power of a Variant of the Looped Transformer.
CoRR, 2024

2023
Continual Learning by Modeling Intra-Class Variation.
Trans. Mach. Learn. Res., 2023

Elucidating The Design Space of Classifier-Guided Diffusion Generation.
CoRR, 2023

Training Energy-Based Models with Diffusion Contrastive Divergences.
CoRR, 2023

ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis.
CoRR, 2023

Boosting Visual-Language Models by Exploiting Hard Samples.
CoRR, 2023

Random Smoothing Regularization in Kernel Gradient Descent Learning.
CoRR, 2023

Deciphering the Projection Head: Representation Evaluation Self-supervised Learning.
CoRR, 2023

Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Complexity Matters: Rethinking the Latent Space for Generative Modeling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization.
Proceedings of the International Conference on Machine Learning, 2023

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Inducing Neural Collapse in Deep Long-tailed Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Understanding Square Loss in Training Overparametrized Neural Network Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Study of Spatial and Temporal Variations of Ionospheric Total Electron Content in Japan, during 2014-2019 and the 2016 Kumamoto Earthquake.
Sensors, 2021

Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting.
CoRR, 2020

2018
Stein Neural Sampler.
CoRR, 2018

2017
Toward Practical Deployment of Fingerprint-Based Indoor Localization.
IEEE Pervasive Comput., 2017

2015
Contour-based Trilateration for Indoor Fingerprinting Localization.
Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems, 2015


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