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Papers
Beyond Heuristic Prompting: A Concept-Guided Bayesian Framework for Zero-Shot Image Recognition
CVPR 2026
Deconvolution in unlinked linear models
JMLR 2026
Neural Mixture Density Processes
CVPR 2026
Partially Observed Structural Causal Models
UAI 2026
Poisson–Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs
UAI 2026
Provable Subspace Identification of Nonlinear Multi-view CCA
UAI 2026
Proxy-Guided Measurement Calibration
CLeaR 2026
Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs
CVPR 2026
Rethinking Latent Variable in Learned Image Compression
WACV 2026
$σ$-Maximal Ancestral Graphs
UAI 2025
An Asymmetric Independence Model for Causal Discovery on Path Spaces
CLeaR 2025
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
ICML 2025
Bi-Level Optimization for Semi-Supervised Learning with Pseudo-Labeling
AAAI 2025
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
ICML 2025
Causal Representation Learning from Multimodal Biomedical Observations
ICLR 2025
Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets
CLeaR 2025
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
ICML 2025
Deep Variational Multivariate Information Bottleneck - A Framework for Variational Losses
JMLR 2025
Degree of Interference: A General Framework For Causal Inference Under Interference
JMLR 2025
Diffusion-Based Conditional Image Editing through Optimized Inference with Guidance
WACV 2025
Diffusion Directed Acyclic Transformer for Non-Autoregressive Machine Translation
ACL 2025
Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models
WACV 2025
Does learning the right latent variables necessarily improve in-context learning?
ICML 2025
Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations
ICLR 2025
Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data
JMLR 2025