Felix Petersen

Orcid: 0000-0002-8040-5184

According to our database1, Felix Petersen authored at least 24 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
TrAct: Making First-layer Pre-Activations Trainable.
CoRR, 2024

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms.
CoRR, 2024

Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation.
CoRR, 2024

CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion.
CoRR, 2024

Uncertainty Quantification via Stable Distribution Propagation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Grounding Everything: Emerging Localization Properties in Vision-Language Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
ISAAC Newton: Input-based Approximate Curvature for Newton's Method.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning by Sorting: Self-supervised Learning with Group Ordering Constraints.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neural Machine Translation for Mathematical Formulae.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Lernen mit differenzierbaren Algorithmen.
Ausgezeichnete Informatikdissertationen, 2022

Learning with Differentiable Algorithms.
PhD thesis, 2022

Learning with Differentiable Algorithms.
CoRR, 2022

Style Agnostic 3D Reconstruction via Adversarial Style Transfer.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Deep Differentiable Logic Gate Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Domain Adaptation meets Individual Fairness. And they get along.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentiable Top-k Classification Learning.
Proceedings of the International Conference on Machine Learning, 2022

Monotonic Differentiable Sorting Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

GenDR: A Generalized Differentiable Renderer.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Post-processing for Individual Fairness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with Algorithmic Supervision via Continuous Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision.
Proceedings of the 38th International Conference on Machine Learning, 2021

2019
AlgoNet: C<sup>∞</sup> Smooth Algorithmic Neural Networks.
CoRR, 2019

Pix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer.
CoRR, 2019

2018
Towards Formula Translation using Recursive Neural Networks.
Proceedings of the Joint Proceedings of the CME-EI, 2018


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