Neural-Guided Equation Discovery
Fuente:
arXiv
Saved in:
| Main Authors: | Brugger, Jannis, Cerrato, Mattia, Richter, David, Derstroff, Cedric, Maninger, Daniel, Mezini, Mira, Kramer, Stefan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Prompting Neural-Guided Equation Discovery Based on Residuals
by: Brugger, Jannis, et al.
Published: (2025)
by: Brugger, Jannis, et al.
Published: (2025)
Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025)
by: Vazaios, Alexandros, et al.
Published: (2025)
Generating and Explaining Corner Cases Using Learnt Probabilistic Lane Graphs
by: Maci, Enrik, et al.
Published: (2023)
by: Maci, Enrik, et al.
Published: (2023)
The Affine Divergence: Aligning Activation Updates Beyond Normalisation
by: Bird, George
Published: (2025)
by: Bird, George
Published: (2025)
Bayesian Optimization in Linear Time
by: Schneider, Jesse, et al.
Published: (2026)
by: Schneider, Jesse, et al.
Published: (2026)
Randomized Approach to Matrix Completion: Applications in Recommendation Systems and Image Inpainting
by: Krajewska, Antonina, et al.
Published: (2024)
by: Krajewska, Antonina, et al.
Published: (2024)
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection
by: Williamson, Dane, et al.
Published: (2025)
by: Williamson, Dane, et al.
Published: (2025)
Aggregating Direct and Indirect Neighbors through Graph Linear Transformations
by: Rosenhoover, Marshall, et al.
Published: (2025)
by: Rosenhoover, Marshall, et al.
Published: (2025)
Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes
by: Uehara, Eichi
Published: (2026)
by: Uehara, Eichi
Published: (2026)
NeurOptimisation: The Spiking Way to Evolve
by: Cruz-Duarte, Jorge Mario, et al.
Published: (2025)
by: Cruz-Duarte, Jorge Mario, et al.
Published: (2025)
Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks
by: Gendron, Gaël, et al.
Published: (2024)
by: Gendron, Gaël, et al.
Published: (2024)
MINERVA: Mutual Information Neural Estimation for Supervised Feature Selection
by: Muvunza, Taurai, et al.
Published: (2025)
by: Muvunza, Taurai, et al.
Published: (2025)
Exploring Prime Number Classification: Achieving High Recall Rate and Rapid Convergence with Sparse Encoding
by: Lee, Serin, et al.
Published: (2024)
by: Lee, Serin, et al.
Published: (2024)
Causal Portfolio Optimization: Principles and Sensitivity-Based Solutions
by: Dominguez, Alejandro Rodriguez
Published: (2025)
by: Dominguez, Alejandro Rodriguez
Published: (2025)
Causal PDE-Control Models for Dynamic Portfolio Optimization with Latent Drivers
by: Dominguez, Alejandro Rodriguez
Published: (2025)
by: Dominguez, Alejandro Rodriguez
Published: (2025)
A Hybrid Model for Stock Market Forecasting: Integrating News Sentiment and Time Series Data with Graph Neural Networks
by: Sadek, Nader, et al.
Published: (2025)
by: Sadek, Nader, et al.
Published: (2025)
Signal from Noise Signal from Noise: A Neural Network-Based Denoising Approach for Measuring Global Financial Spillovers
by: Karasan, Abdullah, et al.
Published: (2025)
by: Karasan, Abdullah, et al.
Published: (2025)
When Reasoning Fails: Evaluating 'Thinking' LLMs for Stock Prediction
by: Sodha, Rakeshkumar H
Published: (2025)
by: Sodha, Rakeshkumar H
Published: (2025)
The Monte Carlo Method and New Device and Architectural Techniques for Accelerating It
by: Petangoda, Janith, et al.
Published: (2025)
by: Petangoda, Janith, et al.
Published: (2025)
Beyond Normality: Reliable A/B Testing with Non-Gaussian Data
by: Gong, Junpeng, et al.
Published: (2025)
by: Gong, Junpeng, et al.
Published: (2025)
Closing the Curvature Gap: Full Transformer Hessians and Their Implications for Scaling Laws
by: Petrov, Egor, et al.
Published: (2025)
by: Petrov, Egor, et al.
Published: (2025)
Emergence of Quantised Representations Isolated to Anisotropic Functions
by: Bird, George
Published: (2025)
by: Bird, George
Published: (2025)
Information-Theoretic Quality Metric of Low-Dimensional Embeddings
by: Gutiérrez-Bernal, Sebastián, et al.
Published: (2025)
by: Gutiérrez-Bernal, Sebastián, et al.
Published: (2025)
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
by: Magnani, Emilia, et al.
Published: (2024)
by: Magnani, Emilia, et al.
Published: (2024)
Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flight
by: Romero, Angel, et al.
Published: (2023)
by: Romero, Angel, et al.
Published: (2023)
Contrastive and Multi-Task Learning on Noisy Brain Signals with Nonlinear Dynamical Signatures
by: Ghosh, Sucheta, et al.
Published: (2026)
by: Ghosh, Sucheta, et al.
Published: (2026)
Scalable and Interpretable Scientific Discovery via Sparse Variational Gaussian Process Kolmogorov-Arnold Networks (SVGP KAN)
by: Ju, Y. Sungtaek
Published: (2025)
by: Ju, Y. Sungtaek
Published: (2025)
Variational Search Distributions
by: Steinberg, Daniel M., et al.
Published: (2024)
by: Steinberg, Daniel M., et al.
Published: (2024)
Rewarding Beliefs, Not Actions: Consistency-Guided Credit Assignment for Long-Horizon Agents
by: Tang, Wenjie, et al.
Published: (2026)
by: Tang, Wenjie, et al.
Published: (2026)
HAPEns: Hardware-Aware Post-Hoc Ensembling for Tabular Data
by: Maier, Jannis, et al.
Published: (2026)
by: Maier, Jannis, et al.
Published: (2026)
A Comparative Analysis of Distributed Linear Solvers under Data Heterogeneity
by: Velasevic, Boris, et al.
Published: (2023)
by: Velasevic, Boris, et al.
Published: (2023)
On the Compatibility of Generative AI and Generative Linguistics
by: Portelance, Eva, et al.
Published: (2024)
by: Portelance, Eva, et al.
Published: (2024)
One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents
by: Hong, Yoosung
Published: (2026)
by: Hong, Yoosung
Published: (2026)
Deep Learning for Solving and Estimating Dynamic Models in Economics and Finance
by: Scheidegger, Simon
Published: (2026)
by: Scheidegger, Simon
Published: (2026)
Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting
by: Lettner, Jan Niklas, et al.
Published: (2026)
by: Lettner, Jan Niklas, et al.
Published: (2026)
Inter-Series Transformer: Attending to Products in Time Series Forecasting
by: Cristian, Rares, et al.
Published: (2024)
by: Cristian, Rares, et al.
Published: (2024)
Bandwidth Selectors on Semiparametric Bayesian Networks
by: Alejandre, Victor, et al.
Published: (2025)
by: Alejandre, Victor, et al.
Published: (2025)
RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
by: Lv, Haochen, et al.
Published: (2025)
by: Lv, Haochen, et al.
Published: (2025)
Binned semiparametric Bayesian networks for efficient kernel density estimation
by: Sojo, Rafael, et al.
Published: (2025)
by: Sojo, Rafael, et al.
Published: (2025)
Transfer learning for nonparametric Bayesian networks
by: Sojo, Rafael, et al.
Published: (2026)
by: Sojo, Rafael, et al.
Published: (2026)
Similar Items
-
Prompting Neural-Guided Equation Discovery Based on Residuals
by: Brugger, Jannis, et al.
Published: (2025) -
Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025) -
Generating and Explaining Corner Cases Using Learnt Probabilistic Lane Graphs
by: Maci, Enrik, et al.
Published: (2023) -
The Affine Divergence: Aligning Activation Updates Beyond Normalisation
by: Bird, George
Published: (2025) -
Bayesian Optimization in Linear Time
by: Schneider, Jesse, et al.
Published: (2026)