Tony Chiang

According to our database, Tony Chiang authored at least 17 papers between 2008 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Measuring Training Variability From Stochastic Optimization Using Robust Nonparametric Testing.

Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate

IEEE J. Sel. Top. Signal Process., October, 2025

Assessing Generative Models for Structured Data.

Reilly Cannon, Nicolette M. Laird, Caesar Vazquez, Andy Lin, Amy Wagler, Tony Chiang

CoRR, March, 2025

Token Embeddings Violate the Manifold Hypothesis.

Michael Robinson, Sourya Dey, Tony Chiang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Understanding Generative AI Content with Embedding Models.

Max Vargas, Reilly Cannon, Andrew Engel, Anand D. Sarwate, Tony Chiang

CoRR, 2024

Measuring model variability using robust non-parametric testing.

Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate

CoRR, 2024

Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models.

Andrew Engel, Zhichao Wang, Natalie Frank, Ioana Dumitriu, Sutanay Choudhury, Anand D. Sarwate, Tony Chiang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Efficient kernel surrogates for neural network-based regression.

Saad Qadeer, Andrew Engel, Adam Tsou, Max Vargas, Panos Stinis, Tony Chiang

CoRR, 2023

Foundation Model's Embedded Representations May Detect Distribution Shift.

Adam Tsou, Max Vargas, Andrew Engel, Tony Chiang

CoRR, 2023

Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks.

Sinjini Banerjee, Reilly Cannon, Tim Marrinan, Tony Chiang, Anand D. Sarwate

CoRR, 2023

Exploring Learned Representations of Neural Networks with Principal Component Analysis.

Amit Harlev, Andrew Engel, Panos Stinis, Tony Chiang

CoRR, 2023

Minibatching Offers Improved Generalization Performance for Second Order Optimizers.

Eric Silk, Swarnita Chakraborty, Nairanjana Dasgupta, Anand D. Sarwate, Andrew Lumsdaine, Tony Chiang

CoRR, 2023

Robust Explanations for Deep Neural Networks via Pseudo Neural Tangent Kernel Surrogate Models.

Andrew Engel, Zhichao Wang, Natalie S. Frank, Ioana Dumitriu, Sutanay Choudhury, Anand D. Sarwate, Tony Chiang

CoRR, 2023

Spectral Evolution and Invariance in Linear-width Neural Networks.

Zhichao Wang, Andrew Engel, Anand D. Sarwate, Ioana Dumitriu, Tony Chiang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

TorchNTK: A Library for Calculation of Neural Tangent Kernels of PyTorch Models.

Andrew Engel, Zhichao Wang, Anand D. Sarwate, Sutanay Choudhury, Tony Chiang

CoRR, 2022

2021

Variability sources and reliability of 3D - FeFETs.

Milan Pesic, Bastien Beltrando, Andrea Padovani, Shruba Gangopadhyay, Muthukumar Kaliappan, Michael Haverty, Marco A. Villena, Enrico Piccinini, Matteo Bertocchi, Tony Chiang, Luca Larcher, Jack Strand, Alexander L. Shluger

Proceedings of the IEEE International Reliability Physics Symposium, 2021

2008

Estimating node degree in bait-prey graphs.

Denise Scholtens, Tony Chiang, Wolfgang Huber, Robert Gentleman

Bioinform., 2008

Rintact: enabling computational analysis of molecular interaction data from the IntAct repository.

Tony Chiang, Nianhua Li, Sandra E. Orchard, Samuel Kerrien, Henning Hermjakob, Robert Gentleman, Wolfgang Huber

Bioinform., 2008