Phillip Lippe

According to our database, Phillip Lippe authored at least 23 papers between 2020 and 2024.

Collaborative distances:

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

2024

Language Agents Meet Causality - Bridging LLMs and Causal World Models.

John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov

CoRR, 2024

NARAIM: Native Aspect Ratio Autoregressive Image Models.

Daniel Gallo Fernández, Robert van der Klis, Razvan-Andrei Matisan, Janusz Partyka, Efstratios Gavves, Samuele Papa, Phillip Lippe

CoRR, 2024

Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall.

Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink

Comput. Biol. Medicine, 2024

How to Train Neural Field Representations: A Comprehensive Study and Benchmark.

Samuele Papa, Riccardo Valperga, David M. Knigge, Miltiadis Kofinas, Phillip Lippe, Jan-Jakob Sonke, Efstratios Gavves

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Towards the Reusability and Compositionality of Causal Representations.

Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane

Proceedings of the Causal Learning and Reasoning, 2024

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

PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers.

Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter

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

Scalable Subset Sampling with Neural Conditional Poisson Networks.

Adeel Pervez, Phillip Lippe, Efstratios Gavves

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Differentiable Mathematical Programming for Object-Centric Representation Learning.

Adeel Pervez, Phillip Lippe, Efstratios Gavves

Proceedings of the Eleventh International Conference on Learning Representations, 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

Weakly supervised causal representation learning.

Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen

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.

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

Proceedings of the International Conference on Machine Learning, 2022

Efficient Neural Causal Discovery without Acyclicity Constraints.

Phillip Lippe, Taco Cohen, Efstratios Gavves

Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning for Fast Cross-Lingual Adaptation in Dependency Parsing.

Anna Langedijk, Verna Dankers, Phillip Lippe, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, Ekaterina Shutova

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models.

Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink

Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Categorical Normalizing Flows via Continuous Transformations.

Phillip Lippe, Efstratios Gavves

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

2020

A Multimodal Framework for the Detection of Hateful Memes.

Phillip Lippe, Nithin Holla, Shantanu Chandra, Santhosh Rajamanickam, Georgios Antoniou, Ekaterina Shutova, Helen Yannakoudakis

CoRR, 2020

Diversifying Task-oriented Dialogue Response Generation with Prototype Guided Paraphrasing.

Phillip Lippe, Pengjie Ren, Hinda Haned, Bart Voorn, Maarten de Rijke

CoRR, 2020

The Hateful Memes Challenge: Competition Report.

Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Casey A. Fitzpatrick, Peter Bull, Greg Lipstein, Tony Nelli, Ron Zhu, Niklas Muennighoff, Riza Velioglu, Jewgeni Rose, Phillip Lippe, Nithin Holla, Shantanu Chandra, Santhosh Rajamanickam, Georgios Antoniou, Ekaterina Shutova, Helen Yannakoudakis, Vlad Sandulescu, Umut Ozertem, Patrick Pantel, Lucia Specia, Devi Parikh

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020