Sindy Löwe

According to our database, Sindy Löwe authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Artificial Kuramoto Oscillatory Neurons.

Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling

CoRR, 2024

Binding Dynamics in Rotating Features.

Sindy Löwe, Francesco Locatello, Max Welling

CoRR, 2024

2023

Image segmentation with traveling waves in an exactly solvable recurrent neural network.

Luisa H. B. Liboni, Roberto C. Budzinski, Alexandra N. Busch, Sindy Löwe, Thomas A. Keller, Max Welling, Lyle E. Muller

CoRR, 2023

BISCUIT: Causal Representation Learning from Binary Interactions.

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Rotating Features for Object Discovery.

Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling

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

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

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Complex-Valued Autoencoders for Object Discovery.

Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling

Trans. Mach. Learn. Res., 2022

iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects.

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves

CoRR, 2022

CITRIS: Causal Identifiability from Temporal Intervened Sequences.

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves

CoRR, 2022

CITRIS: Causal Identifiability from Temporal Intervened Sequences.

Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Stratis Gavves

Proceedings of the International Conference on Machine Learning, 2022

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data.

Sindy Löwe, David Madras, Richard S. Zemel, Max Welling

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Contrastive Predictive Coding for Anomaly Detection.

Puck de Haan, Sindy Löwe

CoRR, 2021

2020

Learning Object-Centric Video Models by Contrasting Sets.

Sindy Löwe, Klaus Greff, Rico Jonschkowski, Alexey Dosovitskiy, Thomas Kipf

CoRR, 2020

2019

Greedy InfoMax for Biologically Plausible Self-Supervised Representation Learning.

Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling

CoRR, 2019

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders.

Paul Bergmann, Sindy Löwe, Michael Fauser, David Sattlegger, Carsten Steger

Proceedings of the 14th International Joint Conference on Computer Vision, 2019

Putting An End to End-to-End: Gradient-Isolated Learning of Representations.

Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling

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