default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMarc Finzi
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c19]Micah Goldblum, Marc Anton Finzi, Keefer Rowan, Andrew Gordon Wilson:
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning. ICML 2024- [c18]Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson:
Non-Vacuous Generalization Bounds for Large Language Models. ICML 2024 - [c17]Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson:
Compute Better Spent: Replacing Dense Layers with Structured Matrices. ICML 2024 - [i20]Shikai Qiu, Andres Potapczynski, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson:
Compute Better Spent: Replacing Dense Layers with Structured Matrices. CoRR abs/2406.06248 (2024) - [i19]Sanae Lotfi, Yilun Kuang, Brandon Amos, Micah Goldblum, Marc Finzi, Andrew Gordon Wilson:
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models. CoRR abs/2407.18158 (2024) - 2023
- [c16]Marc Anton Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson:
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks. ICLR 2023 - [c15]Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson:
The Lie Derivative for Measuring Learned Equivariance. ICLR 2023 - [c14]Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez:
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. ICML 2023: 10136-10152 - [c13]Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson:
Large Language Models Are Zero-Shot Time Series Forecasters. NeurIPS 2023 - [c12]Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson:
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra. NeurIPS 2023 - [i18]Micah Goldblum, Marc Finzi, Keefer Rowan, Andrew Gordon Wilson:
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning. CoRR abs/2304.05366 (2023) - [i17]Marc Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson:
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks. CoRR abs/2304.14994 (2023) - [i16]Marc Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez:
User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. CoRR abs/2306.07526 (2023) - [i15]Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson:
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra. CoRR abs/2309.03060 (2023) - [i14]Nate Gruver, Marc Finzi, Shikai Qiu, Andrew Gordon Wilson:
Large Language Models Are Zero-Shot Time Series Forecasters. CoRR abs/2310.07820 (2023) - [i13]Sanae Lotfi, Marc Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson:
Non-Vacuous Generalization Bounds for Large Language Models. CoRR abs/2312.17173 (2023) - 2022
- [c11]Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson:
Deconstructing the Inductive Biases of Hamiltonian Neural Networks. ICLR 2022 - [c10]Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson:
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. NeurIPS 2022 - [i12]Nate Gruver, Marc Finzi, Samuel Stanton, Andrew Gordon Wilson:
Deconstructing the Inductive Biases of Hamiltonian Neural Networks. CoRR abs/2202.04836 (2022) - [i11]Nate Gruver, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson:
The Lie Derivative for Measuring Learned Equivariance. CoRR abs/2210.02984 (2022) - [i10]Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson:
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. CoRR abs/2211.13609 (2022) - 2021
- [c9]Marc Anton Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. ICLR 2021 - [c8]Marc Finzi, Max Welling, Andrew Gordon Wilson:
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. ICML 2021: 3318-3328 - [c7]Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. ICML 2021: 5279-5289 - [c6]Marc Finzi, Greg Benton, Andrew Gordon Wilson:
Residual Pathway Priors for Soft Equivariance Constraints. NeurIPS 2021: 30037-30049 - [i9]Marc Finzi, Max Welling, Andrew Gordon Wilson:
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. CoRR abs/2104.09459 (2021) - [i8]Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR abs/2106.06695 (2021) - [i7]Marc Finzi, Gregory W. Benton, Andrew Gordon Wilson:
Residual Pathway Priors for Soft Equivariance Constraints. CoRR abs/2112.01388 (2021) - 2020
- [c5]Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson:
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. ICML 2020: 3165-3176 - [c4]Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson:
Semi-Supervised Learning with Normalizing Flows. ICML 2020: 4615-4630 - [c3]Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson:
Learning Invariances in Neural Networks from Training Data. NeurIPS 2020 - [c2]Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. NeurIPS 2020 - [i6]Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson:
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. CoRR abs/2002.12880 (2020) - [i5]Marc Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. CoRR abs/2010.10876 (2020) - [i4]Gregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson:
Learning Invariances in Neural Networks. CoRR abs/2010.11882 (2020) - [i3]Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. CoRR abs/2010.13581 (2020)
2010 – 2019
- 2019
- [c1]Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson:
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average. ICLR (Poster) 2019 - [i2]Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson:
Semi-Supervised Learning with Normalizing Flows. CoRR abs/1912.13025 (2019) - 2018
- [i1]Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson:
Improving Consistency-Based Semi-Supervised Learning with Weight Averaging. CoRR abs/1806.05594 (2018)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-04 01:25 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
