Marc Finzi - RankMe

41 papers A* 13Journal 26Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence. CoRR Marc Finzi, Shikai Qiu, Yiding Jiang, Pavel Izmailov, J. Zico Kolter, Andrew Gordon Wilson
2025	J	`jnl`	Antidistillation Sampling. CoRR Yash Savani, Asher Trockman, Zhili Feng, Yixuan Even Xu, Avi Schwarzschild, Alexander Robey, Marc Finzi, J. Zico Kolter
2025	J	`jnl`	Compute-Optimal LLMs Provably Generalize Better With Scale. CoRR Marc Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J. Zico Kolter, Andrew Gordon Wilson
2025	J	`jnl`	Predicting the Performance of Black-box LLMs through Self-Queries. CoRR Dylan Sam, Marc Finzi, J. Zico Kolter
2024	J	`jnl`	Compute Better Spent: Replacing Dense Layers with Structured Matrices. CoRR Shikai Qiu, Andres Potapczynski, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson
2024	A*	`conf`	Diffusing Differentiable Representations. NeurIPS Yash Savani, Marc Finzi, J. Zico Kolter
2024	J	`jnl`	Diffusing Differentiable Representations. CoRR Yash Savani, Marc Finzi, J. Zico Kolter
2024	A*	`conf`	Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices. NeurIPS Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Charlie Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson
2024	J	`jnl`	Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices. CoRR Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Zixi Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson
2024	A*	`conf`	Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. NeurIPS Sanae Lotfi, Yilun Kuang, Marc Finzi, Brandon Amos, Micah Goldblum, Andrew Gordon Wilson
2024	J	`jnl`	Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. CoRR Sanae Lotfi, Yilun Kuang, Brandon Amos, Micah Goldblum, Marc Finzi, Andrew Gordon Wilson
2023	J	`jnl`	A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks. CoRR Marc Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson
2023	A*	`conf`	CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra. NeurIPS Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson
2023	J	`jnl`	CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra. CoRR Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson
2023	A*	`conf`	Large Language Models Are Zero-Shot Time Series Forecasters. NeurIPS Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson
2023	J	`jnl`	Large Language Models Are Zero-Shot Time Series Forecasters. CoRR Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson
2023	J	`jnl`	Non-Vacuous Generalization Bounds for Large Language Models. CoRR Sanae Lotfi, Marc Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson
2023	J	`jnl`	The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning. CoRR Micah Goldblum, Marc Finzi, Keefer Rowan, Andrew Gordon Wilson
2023	—	`—`	Understanding and Incorporating Mathematical Inductive Biases in Neural Networks Marc Finzi
2023	J	`jnl`	User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. CoRR Marc Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
2022	J	`jnl`	Deconstructing the Inductive Biases of Hamiltonian Neural Networks. CoRR Nate Gruver, Marc Finzi, Samuel Stanton, Andrew Gordon Wilson
2022	A*	`conf`	PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. NeurIPS Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2022	J	`jnl`	PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. CoRR Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2022	J	`jnl`	The Lie Derivative for Measuring Learned Equivariance. CoRR Nate Gruver, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson
2021	A*	`conf`	A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. ICML Marc Finzi, Max Welling, Andrew Gordon Wilson
2021	J	`jnl`	A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. CoRR Marc Finzi, Max Welling, Andrew Gordon Wilson
2021	A*	`conf`	Residual Pathway Priors for Soft Equivariance Constraints. NeurIPS Marc Finzi, Greg Benton, Andrew Gordon Wilson
2021	J	`jnl`	Residual Pathway Priors for Soft Equivariance Constraints. CoRR Marc Finzi, Gregory W. Benton, Andrew Gordon Wilson
2021	A*	`conf`	SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. ICML Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2021	J	`jnl`	SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2020	A*	`conf`	Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. ICML Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. CoRR Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson
2020	A*	`conf`	Learning Invariances in Neural Networks from Training Data. NeurIPS Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Learning Invariances in Neural Networks. CoRR Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2020	J	`jnl`	Probabilistic Numeric Convolutional Neural Networks. CoRR Marc Finzi, Roberto Bondesan, Max Welling
2020	A*	`conf`	Semi-Supervised Learning with Normalizing Flows. ICML Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson
2020	A*	`conf`	Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. NeurIPS Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2020	J	`jnl`	Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. CoRR Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2019	J	`jnl`	Semi-Supervised Learning with Normalizing Flows. CoRR Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson
2019	—	`conf`	There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average. ICLR (Poster) Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson
2018	J	`jnl`	Improving Consistency-Based Semi-Supervised Learning with Weight Averaging. CoRR Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson