Taco Cohen

Daniel Dijkman

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers.

[BibT_eX]

[DOI]

Pim de Haan

Johann Brehmer

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.

[BibT_eX]

[DOI]

Fragkiskos D. Malliaros

CoRR, 2023

FoMo Rewards: Can we cast foundation models as reward functions?

[BibT_eX]

[DOI]

CoRR, 2023

Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation.

[BibT_eX]

[DOI]

Pietro Mazzaglia

Daniel Dijkman

CoRR, 2023

Geometric Algebra Transformers.

[BibT_eX]

[DOI]

CoRR, 2023

BISCUIT: Causal Representation Learning from Binary Interactions.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Geometric Algebra Transformer.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

EDGI: Equivariant Diffusion for Planning with Embodied Agents.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Expressive Power of Geometric Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Equivariant Mesh Attention Networks.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Guest Editorial: Non-Euclidean Machine Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Deconfounded Imitation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Towards a Grounded Theory of Causation for Embodied AI.

[BibT_eX]

[DOI]

CoRR, 2022

iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects.

[BibT_eX]

[DOI]

CoRR, 2022

CITRIS: Causal Identifiability from Temporal Intervened Sequences.

[BibT_eX]

[DOI]

CoRR, 2022

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Weakly supervised causal representation learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A PAC-Bayesian Generalization Bound for Equivariant Networks.

[BibT_eX]

[DOI]

Arash Behboodi

Gabriele Cesa

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CITRIS: Causal Identifiability from Temporal Intervened Sequences.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Transformer-based Transform Coding.

[BibT_eX]

[DOI]

Yinhao Zhu

Yang Yang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient Neural Causal Discovery without Acyclicity Constraints.

[BibT_eX]

[DOI]

Phillip Lippe

Efstratios Gavves

Proceedings of the Tenth International Conference on Learning Representations, 2022

Region-of-Interest Based Neural Video Compression.

[BibT_eX]

[DOI]

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Implicit Neural Video Compression.

[BibT_eX]

[DOI]

CoRR, 2021

Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set.

[BibT_eX]

[DOI]

CoRR, 2021

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

[BibT_eX]

[DOI]

CoRR, 2021

A Combined Deep Learning based End-to-End Video Coding Architecture for YUV Color Space.

[BibT_eX]

[DOI]

CoRR, 2021

Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces.

[BibT_eX]

[DOI]

CoRR, 2021

Overfitting for Fun and Profit: Instance-Adaptive Data Compression.

[BibT_eX]

[DOI]

Ties van Rozendaal

Iris A. M. Huijben

Proceedings of the 9th International Conference on Learning Representations, 2021

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Progressive Neural Image Compression With Nested Quantization And Latent Ordering.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Extending Neural P-frame Codecs for B-frame Coding.

[BibT_eX]

[DOI]

Reza Pourreza

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Skip-Convolutions for Efficient Video Processing.

[BibT_eX]

[DOI]

Amirhossein Habibian

Davide Abati

Babak Ehteshami Bejnordi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Teacher-Student Curriculum Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2020

A Data and Compute Efficient Design for Limited-Resources Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Discrete Distributions by Dequantization.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Jakub M. Tomczak

CoRR, 2020

Natural Graph Networks.

[BibT_eX]

[DOI]

Pim de Haan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Parallelized Rate-Distortion Optimized Quantization Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 22nd IEEE International Workshop on Multimedia Signal Processing, 2020

Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks.

[BibT_eX]

[DOI]

Adeel Pervez

Efstratios Gavves

Proceedings of the 37th International Conference on Machine Learning, 2020

Feedback Recurrent Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Adversarial Distortion for Learned Video Compression.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Lossy Compression with Distortion Constrained Optimization.

[BibT_eX]

[DOI]

Ties van Rozendaal

Guillaume Sautière

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Feedback Recurrent Autoencoder for Video Compression.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

Pulmonary nodule detection in CT scans with equivariant CNNs.

[BibT_eX]

[DOI]

Marysia Winkels

Medical Image Anal., 2019

Covariance in Physics and Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

A General Theory of Equivariant CNNs on Homogeneous Spaces.

[BibT_eX]

[DOI]

Mario Geiger

Maurice Weiler

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Gauge Equivariant Convolutional Networks and the Icosahedral CNN.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Video Compression With Rate-Distortion Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Explorations in Homeomorphic Variational Auto-Encoding.

[BibT_eX]

[DOI]

CoRR, 2018

Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2018

3D G-CNNs for Pulmonary Nodule Detection.

[BibT_eX]

[DOI]

Marysia Winkels

CoRR, 2018

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks).

[BibT_eX]

[DOI]

Mario Geiger

Maurice Weiler

CoRR, 2018

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rotation Equivariant CNNs for Digital Pathology.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

HexaConv.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Spherical CNNs.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Convolutional Networks for Spherical Signals.

[BibT_eX]

[DOI]

CoRR, 2017

Interpretation of microbiota-based diagnostics by explaining individual classifier decisions.

[BibT_eX]

[DOI]

BMC Bioinform., 2017

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Steerable CNNs.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

A New Method to Visualize Deep Neural Networks.

[BibT_eX]

[DOI]

Luisa M. Zintgraf

CoRR, 2016

Group Equivariant Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Transformation Properties of Learned Visual Representations.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Learning Representations, 2015

Harmonic Exponential Families on Manifolds.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Learning the Irreducible Representations of Commutative Lie Groups.

[BibT_eX]

[DOI]