Phillip Lippe

About Phillip Lippe

Phillip Lippe, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at Universiteit van Amsterdam, specializes in the field of Deep Learning, Causality, Causal Representation Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

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

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

Towards the reusability and compositionality of causal representations

Hierarchical Causal Representation Learning

Contrastive object representation learning from temporal data

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

BISCUIT: Causal Representation Learning from Binary Interactions

Rotating Features for Object Discovery

Phillip Lippe Information

University

Position

___

Citations(all)

420

Citations(since 2020)

420

Cited By

7

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

10

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Phillip Lippe Skills & Research Interests

Deep Learning

Causality

Causal Representation Learning

Top articles of Phillip Lippe

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

arXiv preprint arXiv:2212.05023

2022/12/9

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

2024/3/25

Phillip Lippe
Phillip Lippe

H-Index: 2

Efstratios Gavves
Efstratios Gavves

H-Index: 26

Towards the reusability and compositionality of causal representations

2024/3/14

Phillip Lippe
Phillip Lippe

H-Index: 2

Stuart James
Stuart James

H-Index: 6

Hierarchical Causal Representation Learning

2023/10/27

Phillip Lippe
Phillip Lippe

H-Index: 2

Contrastive object representation learning from temporal data

2023/9/28

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

Advances in Neural Information Processing Systems

2024/2/13

BISCUIT: Causal Representation Learning from Binary Interactions

2023/7/2

Rotating Features for Object Discovery

Advances in Neural Information Processing Systems

2024/2/13

Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems

arXiv preprint arXiv:2206.06169

2022/6/13

Scalable Subset Sampling with Neural Conditional Poisson Networks

2023

Phillip Lippe
Phillip Lippe

H-Index: 2

Efstratios Gavves
Efstratios Gavves

H-Index: 26

Differentiable Mathematical Programming for Object-Centric Representation Learning

2023

Phillip Lippe
Phillip Lippe

H-Index: 2

Efstratios Gavves
Efstratios Gavves

H-Index: 26

Complex-valued autoencoders for object discovery

arXiv preprint arXiv:2204.02075

2022/4/5

Weakly Supervised Causal Representation Learning

2022/3/30

Phillip Lippe
Phillip Lippe

H-Index: 2

Taco Cohen
Taco Cohen

H-Index: 20

CITRIS: Causal Identifiability from Temporal Intervened Sequences

2022/6/28

Efficient Neural Causal Discovery without Acyclicity Constraints

arXiv preprint arXiv:2107.10483

2021/7/22

Intervention Design for Causal Representation Learning

2022/7/9

Mesh convolutional neural networks for wall shear stress estimation in 3D artery models

2021/9/27

Meta-learning for fast cross-lingual adaptation in dependency parsing

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics

2021/4/10

Phillip Lippe
Phillip Lippe

H-Index: 2

Helen Yannakoudakis
Helen Yannakoudakis

H-Index: 16

Categorical normalizing flows via continuous transformations

2021/1/12

Phillip Lippe
Phillip Lippe

H-Index: 2

Efstratios Gavves
Efstratios Gavves

H-Index: 26

See List of Professors in Phillip Lippe University(Universiteit van Amsterdam)

Co-Authors

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