QTN-VQC: An End-to-End Learning Framework for Quantum Neural Networks
- Jun Qi
- Chao-Han Huck Yang
- et al.
- 2021
- NeurIPS 2021
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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275 results for Pin-Yu Chen
Pessimistic Model Selection for Offline Deep Reinforcement Learning
- Chao-Han Huck Yang
- Zhengling Qi
- et al.
- 2021
- NeurIPS 2021
Leveraging Adversarial Reprogramming for Novel Structure-constrained Protein Sequence Design
- Devleena Das
- Inkit Padhi
- et al.
- 2021
- NeurIPS 2021
Simple Transparent Adversarial Examples
- Jaydeep Borkar
- Pin-Yu Chen
- 2021
- ICLR 2021
Adversarial Data Augmentation Improves Unsupervised Machine Learning
- Chia-Yi Hsu
- Pin-Yu Chen
- et al.
- 2021
- ICLR 2021
High-Robustness, Low-Transferability Fingerprinting of Neural Networks
- Siyue Wang
- Xiao Wang
- et al.
- 2021
- ICLR 2021
Causal Inference Q-Network: Toward Resilient Reinforcement Learning
- Huck Yang
- I-Te Hung
- et al.
- 2021
- ICLR 2021
Meta Federated Learning
- Omid Aramoon
- Gang Qu
- et al.
- 2021
- ICLR 2021
Toward Non-Singular Robustness of Neural Networks
- Yu-Lin Tsai
- Chia-Yi Hsu
- et al.
- 2021
- ICLR 2021
Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations
- Yu-Lin Tsai
- Chia-Yi Hsu
- et al.
- 2021
- ICLR 2021