Taco Cohen

Orcid: 0000-0003-3072-3405

Affiliations:
  • University of Amsterdam, The Netherlands


According to our database1, Taco Cohen authored at least 66 papers between 2014 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay.
CoRR, 2024

2023
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.
CoRR, 2023

FoMo Rewards: Can we cast foundation models as reward functions?
CoRR, 2023

Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers.
CoRR, 2023

Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation.
CoRR, 2023

Geometric Algebra Transformers.
CoRR, 2023

BISCUIT: Causal Representation Learning from Binary Interactions.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Geometric Algebra Transformer.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Equivariant Mesh Attention Networks.
Trans. Mach. Learn. Res., 2022

Guest Editorial: Non-Euclidean Machine Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Deconfounded Imitation Learning.
CoRR, 2022

Towards a Grounded Theory of Causation for Embodied AI.
CoRR, 2022

iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects.
CoRR, 2022

CITRIS: Causal Identifiability from Temporal Intervened Sequences.
CoRR, 2022

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Weakly supervised causal representation learning.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

Transformer-based Transform Coding.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient Neural Causal Discovery without Acyclicity Constraints.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Region-of-Interest Based Neural Video Compression.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Implicit Neural Video Compression.
CoRR, 2021

Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set.
CoRR, 2021

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.
CoRR, 2021

A Combined Deep Learning based End-to-End Video Coding Architecture for YUV Color Space.
CoRR, 2021

Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces.
CoRR, 2021

Overfitting for Fun and Profit: Instance-Adaptive Data Compression.
Proceedings of the 9th International Conference on Learning Representations, 2021

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs.
Proceedings of the 9th International Conference on Learning Representations, 2021

Progressive Neural Image Compression With Nested Quantization And Latent Ordering.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Extending Neural P-frame Codecs for B-frame Coding.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Skip-Convolutions for Efficient Video Processing.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Teacher-Student Curriculum Learning.
IEEE Trans. Neural Networks Learn. Syst., 2020

A Data and Compute Efficient Design for Limited-Resources Deep Learning.
CoRR, 2020

Learning Discrete Distributions by Dequantization.
CoRR, 2020

Natural Graph Networks.
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.
Proceedings of the 22nd IEEE International Workshop on Multimedia Signal Processing, 2020

Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Feedback Recurrent Autoencoder.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Adversarial Distortion for Learned Video Compression.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Lossy Compression with Distortion Constrained Optimization.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Feedback Recurrent Autoencoder for Video Compression.
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.
Medical Image Anal., 2019

Covariance in Physics and Convolutional Neural Networks.
CoRR, 2019

A General Theory of Equivariant CNNs on Homogeneous Spaces.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

Video Compression With Rate-Distortion Autoencoders.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Explorations in Homeomorphic Variational Auto-Encoding.
CoRR, 2018

Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks.
CoRR, 2018

3D G-CNNs for Pulmonary Nodule Detection.
CoRR, 2018

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks).
CoRR, 2018

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.
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.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

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

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

2017
Convolutional Networks for Spherical Signals.
CoRR, 2017

Interpretation of microbiota-based diagnostics by explaining individual classifier decisions.
BMC Bioinform., 2017

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis.
Proceedings of the 5th International Conference on Learning Representations, 2017

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

2016
A New Method to Visualize Deep Neural Networks.
CoRR, 2016

Group Equivariant Convolutional Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Transformation Properties of Learned Visual Representations.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Harmonic Exponential Families on Manifolds.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Learning the Irreducible Representations of Commutative Lie Groups.
Proceedings of the 31th International Conference on Machine Learning, 2014


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