Marc Finzi

According to our database1, Marc Finzi authored at least 25 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2018
2019
2020
2021
2022
2023
2024
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Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Diffusing Differentiable Representations.
CoRR, 2024

Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices.
CoRR, 2024

Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models.
CoRR, 2024

Compute Better Spent: Replacing Dense Layers with Structured Matrices.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Non-Vacuous Generalization Bounds for Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning.
CoRR, 2023

CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Large Language Models Are Zero-Shot Time Series Forecasters.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems.
Proceedings of the International Conference on Machine Learning, 2023

The Lie Derivative for Measuring Learned Equivariance.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deconstructing the Inductive Biases of Hamiltonian Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Residual Pathway Priors for Soft Equivariance Constraints.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups.
Proceedings of the 38th International Conference on Machine Learning, 2021

Probabilistic Numeric Convolutional Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Learning Invariances in Neural Networks.
CoRR, 2020

Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Invariances in Neural Networks from Training Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Semi-Supervised Learning with Normalizing Flows.
Proceedings of the 37th International Conference on Machine Learning, 2020

Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Improving Consistency-Based Semi-Supervised Learning with Weight Averaging.
CoRR, 2018


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