:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Duval, Francis, Boucher, Jean-Philippe, Pigeon, Mathieu
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2308.01729
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimization of Actuarial Neural Networks with Response Surface Methodology
by: Ariuntugs, Belguutei, et al.
Published: (2024)

Actuarial Learning for Pension Fund Mortality Forecasting
by: de Melo, Eduardo Fraga L., et al.
Published: (2025)

From Data to Uncertainty Sets: a Machine Learning Approach
by: Bertsimas, Dimitris, et al.
Published: (2025)

Neural-Actuarial Longevity Forecasting: Anchoring LSTMs for Explainable Risk Management
by: Rindori, Davide
Published: (2026)

A Bayesian Approach for Prioritising Driving Behaviour Investigations in Telematic Auto Insurance Policies
by: McLeod, Mark, et al.
Published: (2024)

Learning to Count Isomorphisms with Graph Neural Networks
by: Yu, Xingtong, et al.
Published: (2023)

maneuverRecognition -- A Python package for Timeseries Classification in the domain of Vehicle Telematics
by: Schuster, Jonathan, et al.
Published: (2025)

Combining Structural and Unstructured Data: A Topic-based Finite Mixture Model for Insurance Claim Prediction
by: Hou, Yanxi, et al.
Published: (2024)

A Reinforcement Learning-Based Telematic Routing Protocol for the Internet of Underwater Things
by: Homaei, Mohammadhossein, et al.
Published: (2025)

Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation
by: Zhang, Zhaoyang, et al.
Published: (2024)

An Uncertainty Principle for Linear Recurrent Neural Networks
by: François, Alexandre, et al.
Published: (2025)

Aggregated f-average Neural Network applied to Few-Shot Class Incremental Learning
by: Vu, Mathieu, et al.
Published: (2023)

Homomorphism Counts for Graph Neural Networks: All About That Basis
by: Jin, Emily, et al.
Published: (2024)

Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods
by: Follain, Bertille, et al.
Published: (2024)

Transduce: learning transduction grammars for string transformation
by: Frydman, Francis, et al.
Published: (2023)

Enhancing Actuarial Non-Life Pricing Models via Transformers
by: Brauer, Alexej
Published: (2023)

Learning with Fitzpatrick Losses
by: Rakotomandimby, Seta, et al.
Published: (2024)

LAD-BNet: Lag-Aware Dual-Branch Networks for Real-Time Energy Forecasting on Edge Devices
by: Lignier, Jean-Philippe
Published: (2025)

MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
by: Arnal, Charles, et al.
Published: (2023)

Can We Count on LLMs? The Fixed-Effect Fallacy and Claims of GPT-4 Capabilities
by: Ball, Thomas, et al.
Published: (2024)

The Polynomial Counting Capabilities of Message Passing Neural Networks
by: Sälzer, Marco, et al.
Published: (2026)

Improving Virtual Contrast Enhancement using Longitudinal Data
by: Fayolle, Pierre, et al.
Published: (2025)

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results
by: Tahmasebi, Behrooz, et al.
Published: (2020)

Bayesian Multi-Scale Neural Network for Crowd Counting
by: Sagar, Abhinav
Published: (2020)

DecomposeRL: Learning to Ask Useful, Informative, and Diverse Questions for Semi-Supervised, Traceable Claim Verification
by: Dipta, Shubhashis Roy, et al.
Published: (2026)

Adaptive Interpolation-Synthesis for Motion In-Betweening on Keyframe-Based Animation
by: Raël, Anton, et al.
Published: (2026)

Uncertainty-Aware Prediction of Lung Tumor Growth from Sparse Longitudinal CT Data via Bayesian Physics-Informed Neural Networks
by: Kong, Lingfei, et al.
Published: (2026)

Combining YOLO and Visual Rhythm for Vehicle Counting
by: Ribeiro, Victor Nascimento, et al.
Published: (2025)

Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning
by: Hosseinkhan-Boucher, Rémy, et al.
Published: (2025)

Increasing Information for Model Predictive Control with Semi-Markov Decision Processes
by: Hosseinkhan-Boucher, Rémy, et al.
Published: (2025)

Machine Learning with High-Cardinality Categorical Features in Actuarial Applications
by: Avanzi, Benjamin, et al.
Published: (2023)

Quantum Temporal Convolutional Neural Networks for Cross-Sectional Equity Return Prediction: A Comparative Benchmark Study
by: Chen, Chi-Sheng, et al.
Published: (2025)

TEMPO: Transformers for Temporal Disease Progression from Cross-Sectional Data
by: Hao, Hongtao, et al.
Published: (2026)

Local Fragments, Global Gains: Subgraph Counting using Graph Neural Networks
by: Roy, Shubhajit, et al.
Published: (2023)

From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks
by: Coulombe, Philippe Goulet, et al.
Published: (2023)

Combining Causal Models for More Accurate Abstractions of Neural Networks
by: Pîslar, Theodora-Mara, et al.
Published: (2025)

Dual Convexified Convolutional Neural Networks
by: Bai, Site, et al.
Published: (2022)

Hybrid Deep Convolutional Neural Networks Combined with Autoencoders And Augmented Data To Predict The Look-Up Table 2006
by: Djeddou, Messaoud, et al.
Published: (2024)

Flow Matching for Count Data
by: Wei, Ganchao, et al.
Published: (2026)

Causality is Key for Interpretability Claims to Generalise
by: Joshi, Shruti, et al.
Published: (2026)