Cover Image

Causal Neural Probabilistic Circuits

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Weixin, Zhao, Han
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
by: Chen, Weixin, et al.
Published: (2025)

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning
by: Chen, Weixin, et al.
Published: (2025)

On the Expressive Power of Tree-Structured Probabilistic Circuits
by: Yin, Lang, et al.
Published: (2024)

Probabilistic Neural Circuits
by: Martires, Pedro Zuidberg Dos
Published: (2024)

Neural Network Approximators for Marginal MAP in Probabilistic Circuits
by: Arya, Shivvrat, et al.
Published: (2024)

Neuronal Stochastic Attention Circuit (NSAC) for Probabilistic Representation Learning
by: Razzaq, Waleed, et al.
Published: (2026)

Restructuring Tractable Probabilistic Circuits
by: Zhang, Honghua, et al.
Published: (2024)

Soft Learning Probabilistic Circuits
by: Ghandi, Soroush, et al.
Published: (2024)

Sparse Probabilistic Graph Circuits
by: Rektoris, Martin, et al.
Published: (2025)

Probabilistic Circuits for Cumulative Distribution Functions
by: Broadrick, Oliver, et al.
Published: (2024)

Tractable Representation Learning with Probabilistic Circuits
by: Braun, Steven, et al.
Published: (2025)

The Expressivity Boundary of Probabilistic Circuits: A Comparison with Large Language Models
by: Zhao, Zhiyu, et al.
Published: (2026)

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
by: Komanduri, Aneesh, et al.
Published: (2024)

Probabilistic Circuits with Constraints via Convex Optimization
by: Ghandi, Soroush, et al.
Published: (2024)

Tractable Sharpness-Aware Learning of Probabilistic Circuits
by: Suresh, Hrithik, et al.
Published: (2025)

On the Relationship Between Monotone and Squared Probabilistic Circuits
by: Wang, Benjie, et al.
Published: (2024)

Hyperparameter Optimization via Interacting with Probabilistic Circuits
by: Seng, Jonas, et al.
Published: (2025)

Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
by: Papež, Milan, et al.
Published: (2025)

Geometry-Aware Probabilistic Circuits via Voronoi Tessellations
by: Sidheekh, Sahil, et al.
Published: (2026)

Scaling Up Probabilistic Circuits by Latent Variable Distillation
by: Liu, Anji, et al.
Published: (2022)

Optimal Transport for Probabilistic Circuits
by: Ciotinga, Adrian, et al.
Published: (2024)

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation
by: Chen, Weixin, et al.
Published: (2026)

Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits
by: Gala, Gennaro, et al.
Published: (2024)

A Unified Framework for Human-Allied Learning of Probabilistic Circuits
by: Karanam, Athresh, et al.
Published: (2024)

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits
by: Sidheekh, Sahil, et al.
Published: (2024)

SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regularized Reinforcement Learning
by: Ju, Y. Sungtaek
Published: (2026)

GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
by: Wang, Xiaoqi, et al.
Published: (2022)

A Sobering Look at Tabular Data Generation via Probabilistic Circuits
by: Scassola, Davide, et al.
Published: (2026)

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models
by: Lucas, Peter J. F., et al.
Published: (2026)

Can LLMs Assist Expert Elicitation for Probabilistic Causal Modeling?
by: Shaposhnyk, Olha, et al.
Published: (2025)

COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
by: Kang, Mintong, et al.
Published: (2024)

Graph Neural Network Causal Explanation via Neural Causal Models
by: Behnam, Arman, et al.
Published: (2024)

Neural Causal Abstractions
by: Xia, Kevin, et al.
Published: (2024)

CauScale: Neural Causal Discovery at Scale
by: Peng, Bo, et al.
Published: (2026)

Causal Unit Selection using Tractable Arithmetic Circuits
by: Huang, Haiying, et al.
Published: (2024)

Are Heterogeneous Graph Neural Networks Truly Effective? A Causal Perspective
by: Yang, Xiao, et al.
Published: (2025)

Causal Graph Neural Networks for Wildfire Danger Prediction
by: Zhao, Shan, et al.
Published: (2024)

On the Probabilistic Learnability of Compact Neural Network Preimage Bounds
by: Marzari, Luca, et al.
Published: (2025)

Neural Probabilistic Logic Learning for Knowledge Graph Reasoning
by: Sun, Fengsong, et al.
Published: (2024)

Consistency of Neural Causal Partial Identification
by: Tan, Jiyuan, et al.
Published: (2024)