Tsui-Wei Weng

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 66

Top Topics

Activation Function

Top Venues

Publications

Ge Yan, Yaniv Romano, Tsui-Wei Weng
Provably Robust Conformal Prediction with Improved Efficiency. ICLR (2024)
Ge Yan, Yaniv Romano, Tsui-Wei Weng
Provably Robust Conformal Prediction with Improved Efficiency. CoRR (2024)
Tuomas P. Oikarinen, Tsui-Wei Weng
Linear Explanations for Individual Neurons. CoRR (2024)
Nicholas Bai, Rahul A. Iyer, Tuomas P. Oikarinen, Tsui-Wei Weng
Describe-and-Dissect: Interpreting Neurons in Vision Networks with Language Models. CoRR (2024)
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
Prediction without Preclusion: Recourse Verification with Reachable Sets. ICLR (2024)
Chung-En Sun, Tuomas P. Oikarinen, Tsui-Wei Weng
Crafting Large Language Models for Enhanced Interpretability. CoRR (2024)
Chung-En Sun, Sicun Gao, Tsui-Wei Weng
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents. CoRR (2024)
Tung-Yu Wu, Yu-Xiang Lin, Tsui-Wei Weng
AND: Audio Network Dissection for Interpreting Deep Acoustic Models. CoRR (2024)
Alex Gu, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Certified Interpretability Robustness for Class Activation Mapping. CoRR (2023)
Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. CoRR (2023)
Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng
Attacking c-MARL More Effectively: A Data Driven Approach. ICDM (2023)
Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. CoRR (2023)
Divyansh Srivastava, Tuomas P. Oikarinen, Tsui-Wei Weng
Corrupting Neuron Explanations of Deep Visual Features. ICCV (2023)
Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. ICML (2023)
Tuomas P. Oikarinen, Tsui-Wei Weng
CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks. ICLR (2023)
Divyansh Srivastava, Tuomas P. Oikarinen, Tsui-Wei Weng
Corrupting Neuron Explanations of Deep Visual Features. CoRR (2023)
Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng
Label-Free Concept Bottleneck Models. CoRR (2023)
Mohammad Ali Khan, Tuomas P. Oikarinen, Tsui-Wei Weng
Concept-Monitor: Understanding DNN training through individual neurons. CoRR (2023)
Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng
Label-free Concept Bottleneck Models. ICLR (2023)
Wang Zhang, Ziwen Ma, Subhro Das, Tsui-Wei Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
One step closer to unbiased aleatoric uncertainty estimation. CoRR (2023)
Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning. ICLR (2023)
Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng
Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection. Trans. Mach. Learn. Res. 2023 (2023)
Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng
Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches. ICDM (2023)
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
Prediction without Preclusion: Recourse Verification with Reachable Sets. CoRR (2023)
Justin Lee, Tuomas P. Oikarinen, Arjun Chatha, Keng-Chi Chang, Yilan Chen, Tsui-Wei Weng
The Importance of Prompt Tuning for Automated Neuron Explanations. CoRR (2023)
Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng
Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches. CoRR (2023)
Asaf Gendler, Tsui-Wei Weng, Luca Daniel, Yaniv Romano
Adversarially Robust Conformal Prediction. ICLR (2022)
Wei Liao, Ching-Yun Ko, Tsui-Wei Weng, Luca Daniel, Joel Voldman
Facile Prediction of Neutrophil Activation State from Microscopy Images: A New Dataset and Comparative Deep Learning Approaches. ISBI (2022)
Chester Holtz, Tsui-Wei Weng, Gal Mishne
Learning Sample Reweighting for Accuracy and Adversarial Robustness. CoRR (2022)
Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions. CoRR (2022)
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
Finite-sum smooth optimization with SARAH. Comput. Optim. Appl. 82 (3) (2022)
Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions. IROS (2022)
Tuomas P. Oikarinen, Tsui-Wei Weng
CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks. CoRR (2022)
Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng
Evaluating Robustness of Cooperative MARL: A Model-based Approach. CoRR (2022)
Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. ICLR (2021)
Tuomas P. Oikarinen, Wang Zhang, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng
Robust Deep Reinforcement Learning through Adversarial Loss. NeurIPS (2021)
Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. CoRR (2021)
Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng
On the Equivalence between Neural Network and Support Vector Machine. CoRR (2021)
Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng
On the Equivalence between Neural Network and Support Vector Machine. NeurIPS (2021)
Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel
Fast Training of Provably Robust Neural Networks by SingleProp. CoRR (2021)
Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel
Towards Certificated Model Robustness Against Weight Perturbations. AAAI (2020)
Tsui-Wei Weng, Krishnamurthy (Dj) Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control. ICLR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification for Randomized Smoothing. CoRR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
Rethinking Randomized Smoothing for Adversarial Robustness. CoRR (2020)
Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations. CVPR (2020)
Tuomas P. Oikarinen, Tsui-Wei Weng, Luca Daniel
Robust Deep Reinforcement Learning through Adversarial Loss. CoRR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification For Randomized Smoothing. NeurIPS (2020)
Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin
POPQORN: Quantifying Robustness of Recurrent Neural Networks. CoRR (2019)
Yuh-Shyang Wang, Tsui-Wei Weng, Luca Daniel
Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation. CoRR (2019)
Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. IJCAI (2019)
Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Towards Verifying Robustness of Neural Networks Against Semantic Perturbations. CoRR (2019)
Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. CoRR (2019)
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH. CoRR (2019)
Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. AAAI (2019)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie C. Lozano, Cho-Jui Hsieh, Luca Daniel
On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm. GlobalSIP (2018)
Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel
Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR (2018)
Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. CoRR (2018)
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
Efficient Neural Network Robustness Certification with General Activation Functions. NeurIPS (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. ICLR (Poster) (2018)
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
Efficient Neural Network Robustness Certification with General Activation Functions. CoRR (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. CoRR (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie C. Lozano, Cho-Jui Hsieh, Luca Daniel
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. CoRR (2018)
Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon
Towards Fast Computation of Certified Robustness for ReLU Networks. ICML (2018)
Tsui-Wei Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Ivan V. Oseledets, Luca Daniel
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach. CoRR (2018)
Zheng Zhang, Tsui-Wei Weng, Luca Daniel
A Big-Data Approach to Handle Process Variations: Uncertainty Quantification by Tensor Recovery. CoRR (2016)
Zheng Zhang, Tsui-Wei Weng, Luca Daniel
A Big-Data Approach to Handle Many Process Variations: Tensor Recovery and Applications. CoRR (2016)