Phillip Lippe

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 33

Top Topics

Causal Discovery

Weakly Supervised Learning

Temporal Association Rules

Top Venues

Publications

Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall. Comput. Biol. Medicine 173 (2024)
Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane
Towards the Reusability and Compositionality of Causal Representations. CLeaR (2024)
Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue, Sara Magliacane
Towards the Reusability and Compositionality of Causal Representations. CoRR (2024)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
BISCUIT: Causal Representation Learning from Binary Interactions. UAI (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems. ICLR (2023)
Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
Rotating Features for Object Discovery. CoRR (2023)
Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. CoRR (2023)
Adeel Pervez, Phillip Lippe, Efstratios Gavves
Scalable Subset Sampling with Neural Conditional Poisson Networks. ICLR (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
BISCUIT: Causal Representation Learning from Binary Interactions. CoRR (2023)
Adeel Pervez, Phillip Lippe, Efstratios Gavves
Differentiable Mathematical Programming for Object-Centric Representation Learning. ICLR (2023)
Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter
PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. NeurIPS (2023)
Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
Rotating Features for Object Discovery. NeurIPS (2023)
Samuele Papa, Riccardo Valperga, David M. Knigge, Miltiadis Kofinas, Phillip Lippe, Jan-Jakob Sonke, Efstratios Gavves
How to Train Neural Field Representations: A Comprehensive Study and Benchmark. CoRR (2023)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
CITRIS: Causal Identifiability from Temporal Intervened Sequences. CoRR (2022)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects. CoRR (2022)
Johann Brehmer, Pim de Haan, Phillip Lippe, Taco Cohen
Weakly supervised causal representation learning. CoRR (2022)
Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Stratis Gavves
CITRIS: Causal Identifiability from Temporal Intervened Sequences. ICML (2022)
Phillip Lippe, Taco Cohen, Efstratios Gavves
Efficient Neural Causal Discovery without Acyclicity Constraints. ICLR (2022)
Adeel Pervez, Phillip Lippe, Efstratios Gavves
Differentiable Mathematical Programming for Object-Centric Representation Learning. CoRR (2022)
Anna Langedijk, Verna Dankers, Phillip Lippe, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, Ekaterina Shutova
Meta-Learning for Fast Cross-Lingual Adaptation in Dependency Parsing. ACL (1) (2022)
Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
Complex-Valued Autoencoders for Object Discovery. CoRR (2022)
Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
Complex-Valued Autoencoders for Object Discovery. Trans. Mach. Learn. Res. 2022 (2022)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall. CoRR (2022)
Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen
Weakly supervised causal representation learning. NeurIPS (2022)
Phillip Lippe, Efstratios Gavves
Categorical Normalizing Flows via Continuous Transformations. ICLR (2021)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models. STACOM@MICCAI (2021)
Anna Langedijk, Verna Dankers, Phillip Lippe, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, Ekaterina Shutova
Meta-learning for fast cross-lingual adaptation in dependency parsing. CoRR (2021)
Julian Suk, Pim de Haan, Phillip Lippe, Christoph Brune, Jelmer M. Wolterink
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models. CoRR (2021)
Phillip Lippe, Taco Cohen, Efstratios Gavves
Efficient Neural Causal Discovery without Acyclicity Constraints. CoRR (2021)
Phillip Lippe, Nithin Holla, Shantanu Chandra, Santhosh Rajamanickam, Georgios Antoniou, Ekaterina Shutova, Helen Yannakoudakis
A Multimodal Framework for the Detection of Hateful Memes. CoRR (2020)
Phillip Lippe, Pengjie Ren, Hinda Haned, Bart Voorn, Maarten de Rijke
Diversifying Task-oriented Dialogue Response Generation with Prototype Guided Paraphrasing. CoRR (2020)
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
The Hateful Memes Challenge: Competition Report. NeurIPS (Competition and Demos) (2020)
Phillip Lippe, Efstratios Gavves
Categorical Normalizing Flows via Continuous Transformations. CoRR (2020)