InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification. - Léonard Boussioux; Tomás Giro-Larraz; Charles Guille-Escuret; Mehdi Cherti; Balázs Kégl (CoRR, 2019)

Avoidance Learning Using Observational Reinforcement Learning. - David Venuto; Léonard Boussioux; Junhao Wang; Rola Dali; Jhelum Chakravorty; Yoshua Bengio; Doina Precup (CoRR, 2019)

Combating False Negatives in Adversarial Imitation Learning (Student Abstract). - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (AAAI, 2020)

Asymptotic Cross-Entropy Weighting and Guided-Loss in Supervised Hierarchical Setting using Deep Attention Network. - Charles A. Kantor; Brice Rauby; Léonard Boussioux; Emmanuel Jehanno; André-Philippe Drapeau Picard; Maxim Larrivée; Hugues Talbot (AI4SG@AAAI Fall Symposium, 2020)

oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions. - David Venuto; Jhelum Chakravorty; Léonard Boussioux; Junhao Wang; Gavin McCracken; Doina Precup (CoRR, 2020)

Hurricane Forecasting: A Novel Multimodal Machine Learning Framework. - Léonard Boussioux; Cynthia Zeng; Théo Guénais; Dimitris Bertsimas (CoRR, 2020)

Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction. - Charles A. Kantor; Léonard Boussioux; Brice Rauby; Hugues Talbot (AAAI, 2021)

Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks. - Charles A. Kantor; Léonard Boussioux; Brice Rauby; Hugues Talbot (AAAI, 2021)

Combating False Negatives in Adversarial Imitation Learning. - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (IJCNN, 2021)

Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification. - Charles A. Kantor; Marta Skreta; Brice Rauby; Léonard Boussioux; Emmanuel Jehanno; Alexandra Luccioni; David Rolnick; Hugues Talbot (CoRR, 2021)

TabText: a Systematic Approach to Aggregate Knowledge Across Tabular Data Structures. - Dimitris Bertsimas; Kimberly Villalobos Carballo; Yu Ma; Liangyuan Na; Léonard Boussioux; Cynthia Zeng; Luis R. Soenksen; Ignacio Fuentes (CoRR, 2022)

Integrated multimodal artificial intelligence framework for healthcare applications. - Luis R. Soenksen; Yu Ma; Cynthia Zeng; Léonard Boussioux; Kimberly Villalobos Carballo; Liangyuan Na; Holly M. Wiberg; Michael Lingzhi Li; Ignacio Fuentes; Dimitris Bertsimas (npj Digit. Medicine, 2022)

Reducing Air Pollution through Machine Learning. - Dimitris Bertsimas; Léonard Boussioux; Cynthia Zeng (CoRR, 2023)

Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach. - Dimitris Bertsimas; Léonard Boussioux (CoRR, 2023)

The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations. - Charles Ayoubi; Léonard Boussioux; Yinghao Chen; Justin Ho; Katherine Jackson; Jacquelin Lane; Camila Lin; Rebecca Spens (ICIS, 2024)

From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto. - Segev Wasserkrug; Léonard Boussioux; Dick den Hertog; Farzaneh Mirzazadeh; S. Ilker Birbil; Jannis Kurtz; Donato Maragno (CoRR, 2024)

Holistic deep learning. - Dimitris Bertsimas; Kimberly Villalobos Carballo; Léonard Boussioux; Michael Lingzhi Li; Alex Paskov; Ivan S. Paskov (Mach. Learn., 2024)

Enhancing Decision Making Through the Integration of Large Language Models and Operations Research Optimization. - Segev Wasserkrug; Léonard Boussioux; Dick den Hertog; Farzaneh Mirzazadeh; S. Ilker Birbil; Jannis Kurtz; Donato Maragno (AAAI, 2025)