news
| Oct 20, 2024 | I am attending SIAM MDS this week here in Atlanta. Andreas Robertson and I are organizing a minisymposium on (higher order) stochastic models in materials science and spatial statistics. Also check out the presentations by Stephen, Qi, Christian, and Shreya! |
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| Oct 14, 2024 | I gave a talk in the Level-Set Seminar at UCLA on information geometric mechanics. |
| Sep 20, 2024 | Joint work with Jessie Liu, Spencer Bryngelson, Tamer Zaki, and Ali Mani on targeted data-driven closure modeling published in Physical Review Fluids. |
| Sep 16, 2024 | I gave a talk in the PSU-Purdue-UMD Joint Seminar on Mathematical Data Science on information geometric mechanics. Thanks to John Harlim for inviting me! |
| Aug 15, 2024 | New paper connecting Möbius inversion to bootstrap bias correction now on the arxiv! It derives new nonasymptotic bounds on bootstrap bias correction by understanding the combinatorial properties of the resampling operator. |
| Jul 18, 2024 | I attended SciCADE 2024 and gave a talk on information geometric regularization in the minisymposium on Discretization Methods Involving Multiple Levels and Scales. |
| Jul 12, 2024 | I gave a talk at the Fourth Symposium on Machine Learning and Dynamical Systems at the Fields institute. |
| Jun 19, 2024 | Joint work with Jiong Chen and Mathieu Desbrun was selected for one of five best technical paper awards at SIGGRAPH ‘24! We use KL-optimal Cholesky factorization as a preconditioner to greatly accelerate the method of fundamental solutions. |
| May 10, 2024 | Joint work with Yifan Chen and Houman Owhadi accepted at Mathematics of Computation. We use Cholesky by KL minimization to implement the GP approach to solving nonlinear PDEs at near-linear computational cost! |
| May 09, 2024 | Joint work with Jiong Chen and Mathieu Desbrun accepted at SIGGRAPH2024. We use Cholesky by KL minimization as a preconditioner enabling highly efficient and scalable computation inversion of Green’s matrices arising in computer graphics. |
| May 04, 2024 | I gave a talk at the Brown University Scientific Computing Seminar and had many great discussions during my visit. Thanks Brendan for hosting me! |
| Dec 28, 2023 | Joint work with Spencer Bryngelson, Jessie Liu, and Ali Mani published at JCP. We use sparse LU recovery to improve the accuracy of the macroscopic forcing method by orders of magnitude! |
| Nov 15, 2023 | I gave a virtual talk at the optimization in Oslo (OiO) seminar at Simula. My talk should appear shortly on the OiO Youtube channel. |
| Nov 12, 2023 | I attended a workshop on applied and computational math at Caltech and gave a talk on information geometric regularization. |
| Nov 07, 2023 | I am attending the workshop on compressible multiphase flows at Stanford and gave a talk on information geometric regularization. Thanks Ali for the invitation! |
| Nov 01, 2023 | Start of our grant on untangling computation using games and statistical inference. Thanks for the support, ONR! |
| Oct 12, 2023 | Joint work with Jessie, Spencer, Tamer, and Ali on the adjoint macroscopic forcing method now on the arxiv. |
| Oct 10, 2023 | I gave a talk at the Minds/CIS seminar at Johns Hopkins. Great to be back in Baltimore after almost 10 years! |
| Sep 25, 2023 | Spencer Bryngelson, Ali Mani, and myself organized a minisymposium on Statistical approaches to closure modeling in computational mechanics at IACM MMLDE-CSET 2023. Ruijia presented our work on information geometric regularization. Collaborator Jessie Liu presented ongoing work on the targeted computation of nonlocal closures via adjoint macroscopic forcing. |
| Sep 21, 2023 | I gave a(n online) talk at MPI MiS + UCLA Math of Machine Learning seminar. Thanks a lot to Guido Montufar for inviting me! |
| Sep 08, 2023 | Work with Houman on the sparse recovery of elliptic solution operators now accepted to SISC. This work exponentially reduces the sample complexity of provably learning elliptic solution operators from input-output pairs. |
| Sep 01, 2023 | Start of our grant on information geometric regularization for simulation and optimization of supersonic flow. Thanks for the support, AFOSR! |
| Aug 28, 2023 | Joint work with Ruijia Cao now on the arxiv! We use ideas from semidefinite programming, information geometry, and geometric hydrodynamics to derive inviscid regularizations of the compressible Euler equation! |
| Aug 28, 2023 | I gave a talk at the PKU math department. Thanks a lot to De Huang for hosting me! |
| Aug 21, 2023 | I am attending ICIAM in Tokyo this week. Please say hi if you’re around and/or attend my talk in the minisymposium on Data-Driven Methods in Scientific Machine Learning. |
| Aug 09, 2023 | Congratulations to Ruijia and Stephen for winning PURA travel and salary awards. |
| Aug 01, 2023 | I am visiting Oak Ridge National Laboratory on August 2-3, giving a talk in the ORNL AI Seminar Series. |
| Jul 27, 2023 | Stephen Huan’s paper on greedy conditional selection of sparsity patterns for KL optimal Cholesky factorization now on the arXiv. Joint work with Joe Guinness, Matthias Katzfuss, and Houman Owhadi. Also check out Stephen’s blog post-style summary of the paper. |
| May 25, 2023 | I gave a talk at Ecole Polytechnique, thanks Mathieu Desbrun for hosting me! |
| Apr 26, 2023 | Paper on variational inference with double KL minimization accepted at ICML 2023! First authors are Jian Cao and Myeongjong Kang from the group of Matthias Katzfuss. |
| Apr 13, 2023 | Congratulations to Stephen Huan for receiving a Summer Undergraduate Research Fellowship (SURF) from Caltech! Congratulations to Qi Zeng for receiving the 2023 Outstanding Undergraduate Researcher Award from the College of Computing at Georgia Tech! |
| Apr 07, 2023 | New paper with Yifan (lead author) and Houman now on the arXiv. We use KL-minimizing Cholesky factorization to accelerate GP-based PDE solvers, resulting in scalable GP-based solvers for general PDEs! |
| Mar 26, 2023 | Matthias’ paper on Bayesian transport maps, was just accepted at JASA T&M! |
| Feb 04, 2023 | Paper on variational inference with double KL minimization now on the arXiv! First authors are Jian Cao and Myeongjong Kang from the group of Matthias Katzfuss. |
| Jan 20, 2023 | Congratulations to Qi Zeng, for getting his paper on Competitive Physics-Informed Networks accepted at ICLR 2023! Joint work with Yash Kothari and Spencer Bryngelson. |
| Jan 20, 2023 | I am giving an invited plenary talk at the Georgia Scientific Computing Symposium (GSCS 2023) on Saturday February 18. |
| Dec 21, 2022 | New version of our paper on the recovery of elliptic solvers from matrix-vector products now on the arXiv. With greatly extended experiments, plenty of new figures, and theoretical results on the recovery of the continuous Green’s function. Joint work with Houman. |
| Nov 30, 2022 | Congratulations to Jiawei for having his paper on ZerO Initialization for deep neural networks accepted at TMLR! |
| Oct 21, 2022 | I am giving a talk at the Computational Mathematics and Scientific Computing Seminar at the Courant Institute. |
| Sep 23, 2022 | I will be at the Siam Conference on the Mathematics of Data Science in San Diego from Sep. 26-30. I’ll give a talk on locality-exploiting operator learning on Friday 11:00-11:25, as part of the minisymposium on “Fast and Scalable Bayesian Inference”. Stephen will also be there, and present his work on experimental design approaches to sparse linear algebra on Wednesday 3:15-3:40 in the minisymposium on “Kernel Methods for Computing and Learning”. |
| Sep 14, 2022 | I gave a talk (virtually) at the seminar for mathematics in imaging, data, and optimization at RPI, thanks to Yangyang for inviting me! You can find the video of the talk here. |
| Jul 15, 2022 | I will be at the CTR summer program from July 17th to August 12th, working with Spencer Bryngelson on using locality and causality for operator inference. Feel free to reach out if you are at Stanford during that time! |
| May 01, 2022 | Competitive physics informed networks solve PDEs to accuracies previously out of reach for physics informed networks! Joint work with Qi Zeng and Spencer Bryngelson. |
| Apr 19, 2022 | I’ll be giving a talk at the UPenn applied mathematics and computational science colloquium on Friday April 22nd. |
| Feb 19, 2022 | I will be giving a (virtual) talk at the Stanford Applied Math Seminar on Feb 23. |
| Nov 28, 2021 | Joint work with Jeffrey, Alistair, Yuanyuan, and Anima now on the arxiv. We extend competitive gradient descent to arbitrary numbers of agents, prove its local convergence, and show that it learns significantly more performant policies when used for multi-agent reinforcement learning. |
| Oct 26, 2021 | Check out Jiawei’s new paper to learn how to initialize residual networks deterministically! |
| Oct 22, 2021 | New paper, joint with Houman, now on the arXiv! We show that the solution operator of elliptic PDEs can be recovered, or learned, from only a polylogarithmic number of matrix-vector products! |
| Sep 21, 2021 | I will be giving a talk at the Emory Scientific Computing Seminar on September 24th at 12:30 pm! |
| Aug 25, 2021 | Check out Matthias’ paper on Bayesian transport maps, fresh on the arXiv! |
| Jun 10, 2021 | In joint work with Jiong Chen, Jin Huang, and Mathieu Desbrun accepted in SIGGRAPH2021, we show how to beat state-of-the-art AMG libraries just by incomplete Cholesky factorization! |
| Jun 07, 2021 | Check out Jing’s paper on robust RL, presented as a poster at L4DC2021! |
| May 19, 2021 | I successfully defended my Ph.D. thesis, you can find a video of the defense here! Starting August 1st 2021, I will join the School of Computational Science and Engineering at Georgia Tech! |
| Sep 23, 2020 | Check out my talk at the Second Symposium on Machine Learning and Dynamical Systems at the Fields institute. |
| Sep 17, 2020 | The ICML 2020 talks are now online! Check out my talk on implicit competitive regularization at the main conference and my talk on competitive mirror descent at the workshop “Beyond first order methods in machine learning systems”. |
| Aug 11, 2020 | Check out my talk at the Bernoulli-IMS One World Symposium 2020. I am talking about joint work with Matthias and Houman on the sparse factorization of dense kernel matrices using Kullback-Leibler minimization. |
| Jul 31, 2020 | I will give a virtual talk at Mila on August 5th, 2:30pm Eastern |
| Jul 31, 2020 | Check out the new blog post on our work on sparse Cholesky factorization of dense kernel matrices. |