| Time |
Speaker |
Title |
| 7/27, 10:30am |
Anna Dawid
Leiden Univ. |
Interpretable machine learning for quantum simulators[Video][CC] |
| 7/28, 10:30am |
Ehsan Khatami
SJSU |
Exploring the Fermi-Hubbard Model with AI Tools[Video][CC] |
| 7/29, 10:30am |
Victor Albert
QuICS |
Research in the AI age: first experiences[Video][CC] |
| 7/30, 10:30am |
Matija Medvidovic
ETH Zurich |
Variational and supervised learning of effective electronic potentials[Video] |
| 7/30, 1:30pm |
Dezhe Jin
Penn State |
Computing with sparse spikes: towards energy-efficient brain-inspired AI[Video][CC] |
| 8/03, 10:30am |
Kartiek Agarwal
ANL |
Learning quantum ground states in the space of measurement outcomes[Video][CC] |
| 8/04, 10:30am |
Juan Carrasquilla Alvarez
ETH Zurich |
Entropy of randomized measurements and estimating it with generative models[Video][CC] |
| 8/04, 1:30pm |
Zhengcheng Gu
(CUHK)
Cheryne Jonay
(Univ. of Ljubljana)
Ying Jer Kao
(NTU)
Xiaoliang Qi
(Stanford)
Chaoxing Liu
(Penn State) |
Discussion: Agents in Quantum Research |
| 8/05, 10:30am |
Antoine Georges
Flatiron Institute |
Does the Hubbard Model Host (High-Tc) Superconductivity?[Video][CC] |
| 8/05, 1:30pm |
Matija Medvidovic
ETH Zurich |
Tutorial on Neural Quantum States[Video] |
| 8/05, 3:00pm |
Antoine Georges
Flatiron Institute |
Open Discussion on Neural Quantum States |
| 8/06, 10:30am |
Agnes Valenti
Flatiron Institute |
From 2D materials to quantum impurity solvers: A neural-network perspective[Video][CC] |
| 8/10, 10:30am |
Masatoshi Imada
Sophia Univ. |
AI/NQS Aided ab initio Studies on Strongly Correlated Electrons ― Cases of Cuprate Superconductors and Quantum Spin Liquids in Molecular Solids[Video][CC] |
| 8/11, 10:30am |
Qimin Yan
Northeastern |
Symmetry-aware and property-constrained generative design of quantum materials[Video] |
| 8/11, 1:30pm |
Miguel Morales Silva
Flatiron Institute |
Insights into the physics of 2D correlated electrons from Neural Quantum States[Video] |
| 8/11, 2:15pm |
Binghai Yan
Penn State |
Altermagnetism: an AI-assisted Quantum Materials Study[Video] |
| 8/12, 10:30am |
Filippo Gaggioli
MIT |
NN-VMC adventures in 2D materials[Video] |
| 8/13, 10:30am |
Ehud Altman
UC Berkeley |
Using generative models to observe measurement induced entanglement and learnability transitions[Video] |
| 8/17, 10:15am |
Estelle Inack
Perimeter Inst. |
Data-enhanced self-learning projection quantum Monte Carlo with Rydberg-atom measurements[Video] |
| 8/18, 10:30am |
Murphy Yuezhen Niu
UCSB |
Machine Learning for Full Stack Quantum Co-Design[Video] |
| 8/18, 1:30pm |
Anna Dawid
(Leiden Univ.)
Giovanni Cemin
(MPI-PKS) |
Blackboard tutorial on reinforcement learning & RL applications in quantum physics |
| 8/19, 10:30am |
Isaac Kim
UC Davis |
Local definition of quantum phases[Video][CC] |
| 8/20, 10:30am |
Timothy Hsieh
Perimeter Inst. |
Decodable and unlearnable phases and transitions[Video][CC] |
| 8/20, 1:30pm |
Eun Ah Kim
Cornell |
AI for quantum simulation towards hybrid learning[Slides][Video][CC] |
| 8/24, 10:15am |
Shiyu Zhou
Perimeter Inst. |
Machine learning quantum phases: from universal classification to autonomous discovery |
| 8/25, 10:30am |
Rouven Koch
TU Delft |
Hamiltonian Learning in Quantum Magnets - From Local Spectroscopy to Microscopic Models[Slides][Video][CC] |
| 8/25, 3:30pm |
Taige Wang
Massachusetts Institute of Technology |
Simulating quantum circuits with neural networks[Video] |
| 8/26, 10:30am |
Roeland Wiersema
Flatiron Institute |
Reliable and Scalable Variational Monte Carlo[Video][CC] |
| 8/27, 10:30am |
Marin Bukov
MPI-PKS |
Reinforcement Learning for Quantum Technology[Slides][Video][CC] |
| 8/27, 3:30pm |
Yubo Yang
(Hofstra)
Conor Smith
(Flatiron Institute) |
NQS simulations meet Moire and semiconductor devices[Video] |
| 8/28, 10:30am |
Jannes Nys
ETH Zurich |
Preparing neural quantum states at finite temperature[Video][CC] |
| 9/01, 1:30pm |
Shiyu Zhou
Perimeter Inst. |
Machine Learning Quantum Phases Toward Autonomous Phase Discovery[Video][CC] |
| 9/03, 1:00pm |
Florian Marquardt
MPL |
Agentic AI for Exploring Quantum Systems[Video][CC] |
| 9/04, 10:30am |
Thomas Kiely
UC Santa Barbara |
Observing Strong-to-Weak Spontaneous Symmetry Breaking with Machine Learning[Video][CC] |
| 9/08, 10:30am |
Maciej Koch Janusz
Haiqu Inc. |
Information Bottleneck for learning the operator content of quantum and classical theories[Video][CC] |
| 9/08, 3:30pm |
Nisarga Paul
Caltech |
Quantum learning theory for condensed matter: learning the Hamiltonian from the dynamical structure factor[Video] |
| 9/09, 10:30am |
Kunal Sharma
IBM |
Learning Ground State Observables from Quantum Experiments[Video][CC] |
| 9/10, 10:30am |
Tomohiro Soejima
NYU |
Large scale neural quantum states reveal the interplay between superconductivity and quantum criticality[Video][CC] |
| 9/14, 12:15pm |
Eliska Greplova
KIND |
More Is Different (With Machine-Learned Calculators)
[Video]
KITP Blackboard Lunch |
| 9/15, 10:15am |
Federico Becca
Univ. of Trieste |
Laughlin and Wigner crystals in the bosonic Hofstadter model with dipolar interactions: can a simple restricted-Boltzmann machine capture them?[Video][CC] |
| 9/16, 10:30am |
Abhinav Deshpande
IBM Research-Almaden |
Pauli peaked circuits[Embargoed] |
| 9/17, 10:30am |
Ian Spielman
JQI |
Nondestructive characterization of laser-cooled atoms using machine learning[Video][CC] |
| 9/17, 3:30pm |
Baris Ozguler
UC Berkeley |
What Do Quantum Error-Correction Records Reveal?[Embargoed] |
| 9/21, 10:15am |
Roger Melko
U. Waterloo |
Neural Scaling Laws and Quantum Models[Video][CC] |
| 9/22, 10:30am |
Yi Zhuang You
UCSD |
Agentic Research: How we organize a project so that Al agents can do real work in it - and so that we can still check what they did & Discussion[Video][CC] |
| 9/23, 10:30am |
Junyu Liu
Pittsburgh |
Understanding LLMs Through Ideas from Theoretical Physics[Video][CC] |
| 9/24, 10:30am |
Alireza Seif
IBM |
Spacetime mitigation of logical errors[Video][CC] |
| 9/24, 3:30pm |
Gabriel Kotliar
Rutgers |
Searching for and finding new strongly correlated electron materials with trained neural tangent kernels and electronic structure methods: a case study[Embargoed] |
| 9/28-10/01 |
Conference: |
Artificial Intelligence at the Quantum Frontier |
| 10/02, 10:30am |
Han Bo |
Exotic Symmetry and Nishimori Structures in Quantum memory[Video][CC] |
| 10/05, 10:30am |
Christopher Roth
Texas |
Neural network wavefunctions give new insight into electron mediated superconductors[Slides][Video][CC] |
| 10/06, 10:30am |
Community Discussion |
Discussions on Automation of Research[Video][CC] |
| 10/07, 3:30pm |
Fangjun Hu
Quera Computing |
Towards Nontrivial Phases in Generative AI[Embargoed] |
| 10/08, 3:30pm |
Wanda Hou
UCSD |
Design a Quantum Data Processing Unit[Embargoed] |
