AAAI 2026 accepted papers on Probabilistic and scientific modeling
183 of the 4,417 papers accepted at AAAI 2026 (4.1%) are on Probabilistic and scientific modeling, compared with 4.7% at AAAI 2025. They fall into 8 topics.
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Topics and papers
Molecules and proteins · 64 papers
- Revisiting the Canonicalization for Fast and Accurate Crystal Tensor Property Prediction (3 citations)
- DiffRefiner: Coarse to Fine Trajectory Planning via Diffusion Refinement with Semantic Interaction for End to End Autonomous Driving (2 citations)
- Geo2Vec: Shape- and Distance-Aware Neural Representation of Geospatial Entities (2 citations)
- Intention-Aware Diffusion Model for Pedestrian Trajectory Prediction (2 citations)
- NucEL: Single-Nucleotide ELECTRA-Style Genomic Pre-training for Efficient and Interpretable Representations (2 citations)
- T2Agent: A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search (2 citations)
- Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models (1 citation)
- Autonomous Concept Drift Threshold Determination (1 citation)
- CycleChemist: A Dual-Pronged Machine Learning Framework for Organic Photovoltaic Discovery (1 citation)
- De Novo Molecular Generation from Mass Spectra via Many-Body Enhanced Diffusion (1 citation)
- Detecting the Future: All-at-Once Event Sequence Forecasting with Horizon Matching (1 citation)
- Disturbance-based Discretization, Differentiable IDS Channel, and an IDS-Correcting Code for DNA-based Storage (1 citation)
and 52 more in the interactive map.
Dynamical systems · 24 papers
- MoCast: Learning Turbulent Motions Under Physical Guidance for Precipitation Nowcasting (2 citations)
- CellStream: Dynamical Optimal Transport Informed Embeddings for Reconstructing Cellular Trajectories from Snapshots Data (1 citation)
- Fault Diagnosis of Irregular Sequences by Adjoint Learning in Continuous-Time Model Space (1 citation)
- Modeling Trend Dynamics with Variational Neural ODEs for Information Popularity Prediction (1 citation)
- NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation (1 citation)
- DCHO: A Decomposition–Composition Framework for Predicting Higher-Order Brain Connectivity to Enhance Diverse Downstream Applications
- Differentiable Sparse Identification of Lagrangian Dynamics
- Efficient Verification and Falsification of ReLU Neural Barrier Certificates
- ElastoGen: 4D Generative Elastodynamics
- Energy-based Autoregressive Generation for Neural Population Dynamics
- HyRNN: Hybrid Recurrent Neural Networks for Approximating Hybrid Dynamical Systems
- Just Few States Are Enough: Randomized Sparse Feedback for Stability of Dynamical Systems
and 12 more in the interactive map.
Differential equations and PDEs · 22 papers
- AdaField: Generalizable Surface Pressure Modeling with Physics-Informed Pre-training and Flow-Conditioned Adaptation (3 citations)
- PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Burst-Sampled Spatiotemporal Dynamics (2 citations)
- A Multi-Objective Optimization Framework for Adaptive Weighting in Physics-Informed Machine Learning (1 citation)
- AirDDE: Multifactor Neural Delay Differential Equations for Air Quality Forecasting (1 citation)
- CNM-UNet: Continuous Ordinary Differential Equations for Medical Image Segmentation (1 citation)
- Cross-Field Interface-Aware Neural Operators for Multiphase Flow Simulation (1 citation)
- Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations (1 citation)
- SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction (1 citation)
- Decoupled Spatiotemporal Forecasting from Extreme Sparse Observations via Quantized Latent Space
- FCMO: A Flow-Curv Mamba Operator for Large-Scale 3D Vehicle Aerodynamics
- FVNet: Harnessing Liquid Neural Dynamics for Lightweight Visual Representation
- Learning Neural Operators from Partial Observations via Latent Autoregressive Modeling
and 10 more in the interactive map.
Causal discovery · 18 papers
- Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants (2 citations)
- KTCF: Actionable Recourse in Knowledge Tracing via Counterfactual Explanations for Education (2 citations)
- Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach (2 citations)
- CausalCLIP: Causally-Informed Feature Disentanglement and Filtering for Generalizable Detection of Generated Images (1 citation)
- Counterfactual Fairness with Imperfect Causal Graphs (1 citation)
- Robust Causal Discovery Under Imperfect Structural Constraints (1 citation)
- Bayesian Network Structural Consensus via Greedy Min-Cut Analysis
- CaTFormer: Causal Temporal Transformer with Dynamic Contextual Fusion for Driving Intention Prediction
- Causal Discovery from Interval-Based Event Sequences
- Causal Structure Learning for Dynamical Systems with Theoretical Score Analysis
- Causal, Strategic, and Combined Responsibility Attribution in Situation Calculus Concurrent Game Structures
- Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
and 6 more in the interactive map.
Uncertainty and Gaussian processes · 16 papers
- Beta Distribution Learning for Reliable Roadway Crash Risk Assessment (3 citations)
- Physics-Informed Multi-Task Learning for Battery State of Health Prediction with Uncertainty Quantification (2 citations)
- Streaming Generated Gaussian Process Experts for Online Learning and Control (1 citation)
- Credal Ensemble Distillation for Uncertainty Quantification
- DEGRE: Dynamic Gating Ensembles for Trust-Aware Rejection in Medical Image Diagnostics
- Exact Shapley Attributions in Quadratic-time for FANOVA Gaussian Processes
- Flow-Induced Diagonal Gaussian Processes
- Gaussian Uncertainty-Driven Multi-Model Fitting with Graph Neural Network
- Impute Missing Entries with Uncertainty
- Practical Global and Local Bounds in Gaussian Process Regression via Chaining
- Scalable Vision-Guided Crop Yield Estimation
- Symmetric Aggregation of Conformity Scores for Efficient Uncertainty Sets
and 4 more in the interactive map.
Treatment effects · 16 papers
- Auxiliary Gene Learning: Spatial Gene Expression Estimation by Auxiliary Gene Selection (1 citation)
- Invariant Feature Learning for Counterfactual Watch-time Prediction in Video Recommendation (1 citation)
- A Causal Target for Learning to Defer Under Hidden Confounding
- Bayesian Meta-Analyses Could Be More: A Case Study in Trial of Labor After a Cesarean-section Outcomes and Complications
- Causal Inference Under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects
- Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: “One Map, Many Trials” in Satellite-Driven Poverty Analysis
- Detecting Unobserved Confounders: A Kernelized Regression Approach
- Diversity Recommendation via Causal Deconfounding of Co-purchase Relations and Counterfactual Exposure
- DSCF: Dual-Source Counterfactual Fusion for High-Dimensional Combinatorial Interventions
- Estimating Online Influence Needs Causal Modeling! Counterfactual Analysis of Misinformation Engagement on Social Media
- Interpolated Stochastic Interventions Based on Propensity Scores, Target Policies and Treatment-Specific Costs
- Learning Subgroups with Maximum Treatment Effects Without Causal Heuristics
and 4 more in the interactive map.
Variational and generative sampling · 13 papers
- Monte Carlo Diffusion for Generalizable Learning-Based RANSAC (1 citation)
- CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement
- DeepRWCap: Neural-Guided Random-Walk Capacitance Solver for IC Design
- EA-VAE: Learning to Reconstruct Dysarthric Speech via Variational Autoencoder with Encoding Alignment
- Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment
- Information Theoretic Optimal Surveillance for Epidemic Prevalence in Networks
- Multimodal Gaussian Mixture Variational Autoencoder with Consistency Regularizations
- Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics
- ShaLa: Multimodal Shared Latent Generative Modelling
- TabGeoFlow: A Geometric Flow Matching Model for Tabular Data Synthesis
- Unsupervised Combinatorial Probabilistic Reasoning: Probabilistic Coin Change Problem
- VITA: Variational Pretraining of Transformers for Climate-Robust Crop Yield Forecasting
and 1 more in the interactive map.
Bayesian optimization · 10 papers
- VALIANT: Prompt Instability for Active Learning in Black-Box Medical Imaging (1 citation)
- Cliqueformer: Model-Based Optimization with Structured Transformers
- Function-on-Function Bayesian Optimization
- HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
- Instance Generation for Meta-Black-Box Optimization Through Latent Space Reverse Engineering
- LAMDA: Two-Phase HPO via Learning Prior from Low-Fidelity Data
- Meta-Black-Box Optimization with Bi-Space Landscape Analysis and Dual-Control Mechanism for SAEA
- Nanoporous Materials Discovery via Search Bias-Guided Surrogate Modeling
- Parametric Pareto Set Learning for Expensive Multi-Objective Optimization
- Quantum Non-Linear Bandit Optimization