Probabilistic Inference in the Era of Tensor Networks and Differential Programming
Fuente:
arXiv
Saved in:
| Main Authors: | Roa-Villescas, Martin, Gao, Xuanzhao, Stuijk, Sander, Corporaal, Henk, Liu, Jin-Guo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
by: Pes, Lorenzo, et al.
Published: (2025)
by: Pes, Lorenzo, et al.
Published: (2025)
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
by: Eissa, Sherif, et al.
Published: (2025)
by: Eissa, Sherif, et al.
Published: (2025)
Tensor-Networks-based Learning of Probabilistic Cellular Automata Dynamics
by: Casagrande, Heitor P., et al.
Published: (2024)
by: Casagrande, Heitor P., et al.
Published: (2024)
Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations
by: Lin, Yuchao, et al.
Published: (2025)
by: Lin, Yuchao, et al.
Published: (2025)
Programming guide for solving constraint satisfaction problems with tensor networks
by: Gao, Xuanzhao, et al.
Published: (2024)
by: Gao, Xuanzhao, et al.
Published: (2024)
Efficient Probabilistic Tensor Networks
by: Hameed, Marawan Gamal Abdel, et al.
Published: (2025)
by: Hameed, Marawan Gamal Abdel, et al.
Published: (2025)
Branch-and-Bound Tensor Networks for Exact Ground-State Characterization
by: Wang, Yijia, et al.
Published: (2026)
by: Wang, Yijia, et al.
Published: (2026)
Integral Formulas for Vector Spherical Tensor Products
by: Heyraud, Valentin, et al.
Published: (2026)
by: Heyraud, Valentin, et al.
Published: (2026)
Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions
by: Hummerich, Sander, et al.
Published: (2025)
by: Hummerich, Sander, et al.
Published: (2025)
Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
by: Zhang, Ziyang, et al.
Published: (2025)
by: Zhang, Ziyang, et al.
Published: (2025)
Deep Tensor Network
by: Zhang, Yifan
Published: (2023)
by: Zhang, Yifan
Published: (2023)
MixFunn: A Neural Network for Differential Equations with Improved Generalization and Interpretability
by: Farias, Tiago de Souza, et al.
Published: (2025)
by: Farias, Tiago de Souza, et al.
Published: (2025)
ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation
by: Chen, Zhuo, et al.
Published: (2023)
by: Chen, Zhuo, et al.
Published: (2023)
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
by: Zaverkin, Viktor, et al.
Published: (2024)
by: Zaverkin, Viktor, et al.
Published: (2024)
Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics
by: Xie, YuQing, et al.
Published: (2026)
by: Xie, YuQing, et al.
Published: (2026)
Application of Tensor Neural Networks to Pricing Bermudan Swaptions
by: Patel, Raj G., et al.
Published: (2023)
by: Patel, Raj G., et al.
Published: (2023)
BI-EqNO: Generalized Approximate Bayesian Inference with an Equivariant Neural Operator Framework
by: Zhou, Xu-Hui, et al.
Published: (2024)
by: Zhou, Xu-Hui, et al.
Published: (2024)
Graph Convolutional Networks for Simulating Multi-phase Flow and Transport in Porous Media
by: Jiang, Jiamin, et al.
Published: (2023)
by: Jiang, Jiamin, et al.
Published: (2023)
The Bayesian Method of Tensor Networks
by: Guo, Erdong, et al.
Published: (2021)
by: Guo, Erdong, et al.
Published: (2021)
Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks
by: Zhai, Jucai, et al.
Published: (2026)
by: Zhai, Jucai, et al.
Published: (2026)
Gradient Enhanced Self-Training Physics-Informed Neural Network (gST-PINN) for Solving Nonlinear Partial Differential Equations
by: Iyer, Narayan S, et al.
Published: (2025)
by: Iyer, Narayan S, et al.
Published: (2025)
Probabilistic Programming with Programmable Variational Inference
by: Becker, McCoy R., et al.
Published: (2024)
by: Becker, McCoy R., et al.
Published: (2024)
Boosting Defect Detection in Manufacturing using Tensor Convolutional Neural Networks
by: Martin-Ramiro, Pablo, et al.
Published: (2023)
by: Martin-Ramiro, Pablo, et al.
Published: (2023)
Explaining Anomalies with Tensor Networks
by: Hohenfeld, Hans, et al.
Published: (2025)
by: Hohenfeld, Hans, et al.
Published: (2025)
Quantum-Classical Machine learning by Hybrid Tensor Networks
by: Liu, Ding, et al.
Published: (2020)
by: Liu, Ding, et al.
Published: (2020)
A Physics-Guided Probabilistic Surrogate Modeling Framework for Digital Twins of Underwater Radiated Noise
by: Deo, Indu Kant, et al.
Published: (2025)
by: Deo, Indu Kant, et al.
Published: (2025)
TLINet: Differentiable Neural Network Temporal Logic Inference
by: Li, Danyang, et al.
Published: (2024)
by: Li, Danyang, et al.
Published: (2024)
CompactifAI: Extreme Compression of Large Language Models using Quantum-Inspired Tensor Networks
by: Tomut, Andrei, et al.
Published: (2024)
by: Tomut, Andrei, et al.
Published: (2024)
Tensorization of neural networks for improved privacy and interpretability
by: Monturiol, José Ramón Pareja, et al.
Published: (2025)
by: Monturiol, José Ramón Pareja, et al.
Published: (2025)
Generative Learning of the Solution of Parametric Partial Differential Equations Using Guided Diffusion Models and Virtual Observations
by: Gao, Han, et al.
Published: (2024)
by: Gao, Han, et al.
Published: (2024)
Tensor Network Estimation of Distribution Algorithms
by: Gardiner, John, et al.
Published: (2024)
by: Gardiner, John, et al.
Published: (2024)
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Projected Neural Differential Equations for Learning Constrained Dynamics
by: White, Alistair, et al.
Published: (2024)
by: White, Alistair, et al.
Published: (2024)
Differentiable Programming for Computational Plasma Physics
by: McGreivy, Nick
Published: (2024)
by: McGreivy, Nick
Published: (2024)
Differentiability in Unrolled Training of Neural Physics Simulators on Transient Dynamics
by: List, Bjoern, et al.
Published: (2024)
by: List, Bjoern, et al.
Published: (2024)
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
by: White, Alistair, et al.
Published: (2023)
by: White, Alistair, et al.
Published: (2023)
Physics Informed Token Transformer for Solving Partial Differential Equations
by: Lorsung, Cooper, et al.
Published: (2023)
by: Lorsung, Cooper, et al.
Published: (2023)
Discovering Interpretable Ordinary Differential Equations from Noisy Data
by: Golder, Rahul, et al.
Published: (2025)
by: Golder, Rahul, et al.
Published: (2025)
Neural Networks for Predicting Permeability Tensors of 2D Porous Media: Comparison of Convolution- and Transformer-based Architectures
by: Vargdal, Sigurd, et al.
Published: (2025)
by: Vargdal, Sigurd, et al.
Published: (2025)
Quantum-Inspired Tensor Neural Networks for Option Pricing
by: Patel, Raj G., et al.
Published: (2022)
by: Patel, Raj G., et al.
Published: (2022)
Similar Items
-
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
by: Pes, Lorenzo, et al.
Published: (2025) -
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
by: Eissa, Sherif, et al.
Published: (2025) -
Tensor-Networks-based Learning of Probabilistic Cellular Automata Dynamics
by: Casagrande, Heitor P., et al.
Published: (2024) -
Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations
by: Lin, Yuchao, et al.
Published: (2025) -
Programming guide for solving constraint satisfaction problems with tensor networks
by: Gao, Xuanzhao, et al.
Published: (2024)