Tony Chiang - RankMe

18 papers A* 2Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Assessing Generative Models for Structured Data. CoRR Reilly Cannon, Nicolette M. Laird, Caesar Vazquez, Andy Lin, Amy Wagler, Tony Chiang
2025	J	`jnl`	Measuring Training Variability From Stochastic Optimization Using Robust Nonparametric Testing. IEEE J. Sel. Top. Signal Process. Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate
2025	J	`jnl`	Token embeddings violate the manifold hypothesis. CoRR Michael Robinson, Sourya Dey, Tony Chiang
2024	A*	`conf`	Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models. ICLR Andrew Engel, Zhichao Wang, Natalie Frank, Ioana Dumitriu, Sutanay Choudhury, Anand D. Sarwate, Tony Chiang
2024	J	`jnl`	Measuring model variability using robust non-parametric testing. CoRR Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate
2024	J	`jnl`	Understanding Generative AI Content with Embedding Models. CoRR Max Vargas, Reilly Cannon, Andrew Engel, Anand D. Sarwate, Tony Chiang
2023	J	`jnl`	Efficient kernel surrogates for neural network-based regression. CoRR Saad Qadeer, Andrew Engel, Adam Tsou, Max Vargas, Panos Stinis, Tony Chiang
2023	J	`jnl`	Exploring Learned Representations of Neural Networks with Principal Component Analysis. CoRR Amit Harlev, Andrew Engel, Panos Stinis, Tony Chiang
2023	J	`jnl`	Foundation Model's Embedded Representations May Detect Distribution Shift. CoRR Adam Tsou, Max Vargas, Andrew Engel, Tony Chiang
2023	J	`jnl`	Minibatching Offers Improved Generalization Performance for Second Order Optimizers. CoRR Eric Silk, Swarnita Chakraborty, Nairanjana Dasgupta, Anand D. Sarwate, Andrew Lumsdaine, Tony Chiang
2023	J	`jnl`	Robust Explanations for Deep Neural Networks via Pseudo Neural Tangent Kernel Surrogate Models. CoRR Andrew Engel, Zhichao Wang, Natalie S. Frank, Ioana Dumitriu, Sutanay Choudhury, Anand D. Sarwate, Tony Chiang
2023	J	`jnl`	Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks. CoRR Sinjini Banerjee, Reilly Cannon, Tim Marrinan, Tony Chiang, Anand D. Sarwate
2023	A*	`conf`	Spectral Evolution and Invariance in Linear-width Neural Networks. NeurIPS Zhichao Wang, Andrew Engel, Anand D. Sarwate, Ioana Dumitriu, Tony Chiang
2022	J	`jnl`	Spectral evolution and invariance in linear-width neural networks. CoRR Zhichao Wang, Andrew Engel, Anand D. Sarwate, Ioana Dumitriu, Tony Chiang
2022	J	`jnl`	TorchNTK: A Library for Calculation of Neural Tangent Kernels of PyTorch Models. CoRR Andrew Engel, Zhichao Wang, Anand D. Sarwate, Sutanay Choudhury, Tony Chiang
2021	—	`conf`	Variability sources and reliability of 3D - FeFETs. IRPS 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
2008	J	`jnl`	Estimating node degree in bait-prey graphs. Bioinform. Denise Scholtens, Tony Chiang, Wolfgang Huber, Robert Gentleman
2008	J	`jnl`	Rintact: enabling computational analysis of molecular interaction data from the IntAct repository. Bioinform. Tony Chiang, Nianhua Li, Sandra E. Orchard, Samuel Kerrien, Henning Hermjakob, Robert Gentleman, Wolfgang Huber