Felix Petersen
18 papers · 2021–2025 · 7 conferences · across top CS/AI conferences
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NIPS (7)
ICLR (4)
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ACL (1)
ICCV (1)
WACV (1)
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Keywords
gradient descent
(3)
differentiable programming
(3)
algorithmic fairness
(2)
neural network
(2)
3d reconstruction
(2)
convolutional neural network
(2)
differentiable sorting
(2)
individual fairness
(2)
logic gate network
(2)
domain adaptation
(2)
differentiable rendering
(2)
weakly supervised learning
(1)
adversarial learning
(1)
neural machine translation
(1)
self-supervised learning
(1)
style transfer
(1)
semantic segmentation
(1)
neural network optimization
(1)
graph laplacian
(1)
zero-shot learning
(1)
Papers
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
ICLR 2025
Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms
NIPS 2024
Uncertainty Quantification via Stable Distribution Propagation
ICLR 2024
Grounding Everything: Emerging Localization Properties in Vision-Language Transformers
CVPR 2024
TrAct: Making First-layer Pre-Activations Trainable
NIPS 2024
Convolutional Differentiable Logic Gate Networks
NIPS 2024
ISAAC Newton: Input-based Approximate Curvature for Newton's Method
ICLR 2023
Learning by Sorting: Self-supervised Learning with Group Ordering Constraints
ICCV 2023
Neural Machine Translation for Mathematical Formulae
ACL 2023
Style Agnostic 3D Reconstruction via Adversarial Style Transfer
WACV 2022
Deep Differentiable Logic Gate Networks
NIPS 2022
Domain Adaptation meets Individual Fairness. And they get along.
NIPS 2022
GenDR: A Generalized Differentiable Renderer
CVPR 2022
Monotonic Differentiable Sorting Networks
ICLR 2022
Differentiable Top-k Classification Learning
ICML 2022
Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
ICML 2021
Learning with Algorithmic Supervision via Continuous Relaxations
NIPS 2021
Post-processing for Individual Fairness
NIPS 2021