Yaron Lipman

37 papers · 2015–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🏃 Academic Marathon (10) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (6) 🏆 Keyword Champion (6) 👑 Triple Crown 🤝 Dynamic Duo (12) 🧬 Topic Evolution 🗃️ Keyword Collector (114) 💎 Century Club (37) 🔥 Unstoppable (8) 📈 Trend Setter ⚡ Prolific Year (5)

Conferences

ICML (11) ICLR (10) NIPS (10) CVPR (3) ICCV (2) JMLR (1)

Top co-authors

Ricky T. Q. Chen (12) Haggai Maron (9) Heli Ben-Hamu (8) Matan Atzmon (7) Lior Yariv (7) Neta Shaul (6) Itai Gat (4) Brian Karrer (4) Nimrod Segol (4) Maximilian Nickel (4)

Keywords

implicit neural representation (6) neural network (5) generative model (5) surface reconstruction (4) 3d reconstruction (3) signed distance function (3) graph neural network (3) point cloud (3) probability path (3) optimal transport (2) continuous normalizing flow (2) normalizing flow (2) diffusion model (2) graph isomorphism (2) convex optimization (2) flow matching (2) novel view synthesis (2) expressive power (2) graph representation learning (1) adversarial robustness (1)

Papers

Generator Matching: Generative modeling with arbitrary Markov processes ICLR 2025

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective ICLR 2025

Flow Matching on General Geometries ICLR 2024

Bespoke Solvers for Generative Flow Models ICLR 2024

Generalized Schrödinger Bridge Matching ICLR 2024

Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models ICML 2024

Discrete Flow Matching NIPS 2024

D-Flow: Differentiating through Flows for Controlled Generation ICML 2024

Mosaic-SDF for 3D Generative Models CVPR 2024

Flow Matching for Generative Modeling ICLR 2023

MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation ICML 2023

Equivariant Polynomials for Graph Neural Networks ICML 2023

Multisample Flow Matching: Straightening Flows with Minibatch Couplings ICML 2023

Weisfeiler and Leman go Machine Learning: The Story so far JMLR 2023

On Kinetic Optimal Probability Paths for Generative Models ICML 2023

Frame Averaging for Invariant and Equivariant Network Design ICLR 2022

VisCo Grids: Surface Reconstruction with Viscosity and Coarea Grids NIPS 2022

Neural Conservation Laws: A Divergence-Free Perspective NIPS 2022

Frame Averaging for Equivariant Shape Space Learning CVPR 2022

Matching Normalizing Flows and Probability Paths on Manifolds ICML 2022

SALD: Sign Agnostic Learning with Derivatives ICLR 2021

Riemannian Convex Potential Maps ICML 2021

Phase Transitions, Distance Functions, and Implicit Neural Representations ICML 2021

Moser Flow: Divergence-based Generative Modeling on Manifolds NIPS 2021

Volume Rendering of Neural Implicit Surfaces NIPS 2021

SAL: Sign Agnostic Learning of Shapes From Raw Data CVPR 2020

Set2Graph: Learning Graphs From Sets NIPS 2020

On Universal Equivariant Set Networks ICLR 2020

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance NIPS 2020

Implicit Geometric Regularization for Learning Shapes ICML 2020

On the Universality of Invariant Networks ICML 2019

Controlling Neural Level Sets NIPS 2019

Provably Powerful Graph Networks NIPS 2019

Invariant and Equivariant Graph Networks ICLR 2019

Surface Networks via General Covers ICCV 2019

(Probably) Concave Graph Matching NIPS 2018

Wide Baseline Stereo Matching With Convex Bounded Distortion Constraints ICCV 2015