6:00 a.m. - 6:05 a.m. |
Opening Remarks |
6:05 a.m. - 6:35 a.m. |
Invited talk 1: Jens Eisert
Tensor Networks as a Data Structure in Probabilistic Modeling and for Learning Dynamical Laws from Data
|
6:35 a.m. - 6:45 a.m. |
Q&A |
6:45 a.m. - 7:17 a.m. |
Invited talk 2: Nadav Cohen
Expressiveness in Deep Learning via Tensor Networks and Quantum Entanglement
|
7:17 a.m. - 7:25 a.m. |
Q&A |
7:25 a.m. - 7:55 a.m. |
Invited talk 3: Frank Verstraete
Tensor Networks and Counting Problems on the Lattice
|
7:55 a.m. - 8:05 a.m. |
Q&A |
8:05 a.m. - 8:50 a.m. |
Invited talk 4: Ivan Oseledets
Quantum in ML and ML in Quantum
|
8:50 a.m. - 9:00 a.m. |
Q&A |
9:00 a.m. - 9:40 a.m. |
Invited talk 5: Animashree Anandkumar
Live Presentation By Prof. Anima
|
9:40 a.m. - 10:07 a.m. |
Invited talk 6: Tomotoshi Nishino
A Century of the Tensor Network Formulation from the Ising Model
|
10:07 a.m. - 10:15 a.m |
Q&A |
10:15 a.m. - 10:18 a.m. |
Poster 1: Yao Lei Xu
Multi-Graph Tensor Networks
|
10:18 a.m. - 10:21 a.m. |
Poster 2: Hong Hao
High Performance Single-Site Finite DMRG on GPUs
|
10:21 a.m. - 10:24 a.m. |
Poster 3: Yunpu Ma
Variational Quantum Circuit Model for Knowledge Graph Embeddings
|
10:24 a.m. - 10:27 a.m. |
Poster 4: Yen-Chi Chen
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
|
10:27 a.m. - 10:30 a.m. |
Poster 5: Hui Gao
A Neural Matching Model based on Quantum Interference and Quantum Many-body System
|
10:30 a.m. - 10:40 a.m. |
Contributed talk 1: Alex Goeßmann
Paper 3: Tensor network approaches for data-driven identification of non-linear dynamical laws
|
10:40 a.m. - 10:50 a.m. |
Contributed talk 2: Jensen Wang
Paper 6: Anomaly Detections with Tensor Networks
|
10:50 a.m. - 11:00 a.m. |
Contributed talk 3: Chao Li
Paper 32: High-order Learning Model via Fractional Tensor Network Decomposition
|
11:00 a.m. - 11:45 a.m. |
Panel Discussion 1: Jacob Biamonte, Ivan Oseledets, Glen Evenbly, Jens Eisert, Nadav Cohen, Xiao-Yang Liu
Theoretical, Algorithmic and Physical
|
11:45 a.m. - 12:00 p.m. |
Break
|
12:00 p.m. - 12:45 p.m. |
Panel Discussion 2: Glen Evenbly, Martin Ganahl, Paul Springer, Xiao-Yang Liu
Software and High Performance Implementation
|
12:45 p.m. - 1:00 p.m. |
Break
|
1:00 p.m. - 1:28 p.m. |
Invited talk 7: Paul Springer
cuTensor: High-Performance CUDA Tensor Primitives
|
1:28 p.m. - 1:35 p.m. |
Q&A |
1:35 p.m. - 2:05 p.m. |
Invited talk 8: Martin Ganahl
TensorNetwork: A Python Package for Tensor Network Computations
|
2:05 p.m. - 2:15 p.m. |
Q&A |
2:15 p.m. - 2:51 p.m. |
Invited talk 9: Guillaume Rabusseau
Tensor Network Models for Structured Data
|
2:51 p.m. - 3:00 p.m. |
Q&A |
3:00 p.m. - 3:30 p.m. |
Invited talk 10: Glen Evenbly
Getting Started with Tensor Networks
|
3:30 p.m. - 3:40 p.m. |
Q&A |
3:40 p.m. - 3:50 p.m. |
Contributed talk 4: Khadijeh Najafi
Paper 27: Limitations of gradient-based Born Machine over tensornetworks on learning quantum nonlocality
|
3:50 p.m. - 4:00 p.m. |
Contributed talk 5: Philip Blagoveschensky
Paper 19: Deep convolutional tensor network
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4:00 p.m. - 4:04 p.m. |
Poster 6: Yiming Fang
Paper 16: Quantum Tensor Networks for Variational Reinforcement Learning
|
4:04 p.m. - 4:07 p.m. |
Poster 7: (Poster talk)
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
|
4:07 p.m. - 4:10 p.m. |
Poster 8: Yitong Yao
Paper 24: Modeling Natural Language via Quantum Many-body Wave Function and Tensor Network
|
4:10 p.m. - 4:32 p.m. |
Invited talk 11: Rose Yu
Tensor Methods for Efficient and Interpretable Spatiotemporal Learning
|
4:32 p.m. - 4:40 p.m. |
Q&A |
4:40 p.m. - 5:10 p.m. |
Invited talk 12: Giacomo Torlai
Learning Quantum Channels with Tensor Networks
|
5:10 p.m. - 5:20 p.m. |
Q&A |
5:20 p.m. - 5:50 p.m. |
Invited talk 13: Anwar Walid
(Live Presentation): High Performance Computation for Tensor Networks Learning
|
5:50 p.m. - 5:55 p.m. |
Closing Remarks |