Francesco Alesiani
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    • ACCELERATING PARTICLE SIMULATIONS USING MACHINE LEARNING AND MOLECULAR DYNAMIC SIMULATIONS
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    • Machine learning knowledge management based on lifelong boosting in presence of less data
    • Learning logical rules over graph structured data using message passing
    • Graph Reasoning Networks
    • Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
    • Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials
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    • Partial planar point cloud matching using machine learning with applications in biometric systems
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    • Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
    • CAPE: channel-attention-based PDE parameter embeddings for SciML
    • Continual Invariant Risk Minimization
    • Continual learning of artificial intelligence systems based on bi-level optimization
    • Continuous-Discrete Message Passing for Graph Logic Reasoning
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    • Learning neural pde solvers with parameter-guided channel attention
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    • Method and system to differentiate through bilevel optimization problems using machine learning
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    • BiGrad: Differentiating through bilevel optimization programming
    • Constrained clustering for the capacitated vehicle routing problem (cc-cvrp)
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    • HyperFNO: Improving the generalization behavior of Fourier Neural Operators
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    • Pdebench: An extensive benchmark for scientific machine learning
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    • Optimization of collection and consolidation operations in cross-border multi-modal distribution networks
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    • Learning an interpretable graph structure in multi-task learning
    • Measuring the discrepancy between conditional distributions: Methods, properties and applications
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    • Robust timetable optimization for bus lines subject to resource and regulatory constraints
    • Method for the continuous processing of two-level data on a system with a plurality of nodes
    • Method and system for providing demand-responsive dispatching of a fleet of transportation vehicles, and a mobility-activity processing module for providing a mobility trace database
    • Method for incident detection in a time-evolving system
    • On learning from inaccurate and incomplete traffic flow data
    • Reinforcement learning-based bus holding for high-frequency services
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    • Locally growing rapid tree (LGRT) motion planning for autonomous driving
    • Remote testimony: How to trust an autonomous vehicle
    • A Scenario-Oriented Approach for Noise Detection on Traffic Flow Data
    • Drift3flow: Freeway-incident prediction using real-time learning
    • D2. 13-Final report eCoMessages
    • 2014 Index IEEE Intelligent Transportation Systems Magazine Vol. 6
    • A probabilistic activity model for predicting the mobility patterns of homogeneous social groups based on social network data
    • Educated rules for the prediction of human mobility patterns based on sparse social media and mobile phone data
    • Opportunistic solution-space reduction techniques for reducing the time complexity of dynamic speed control with microsimulation on motorways
    • Optimization of charging stops for fleet of electric vehicles: A genetic approach
    • Afshin Abdi, Qualcomm Milad Abolpour, University of Oulu Ibrahim Abou-Faycal, American University of Beirut Maria Abu-Sini, Technion
    • D242. 213 (D2. 13) Final report ecoMessages
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    • Cooperative ITS messages for green mobility: an overview from the eCoMove project
    • A Scenario-Oriented approach for Noise detection on Traffic Flow data
    • SubProject No. SP2 SubProject Title Core Technology Integration Workpackage No. WP2. 5 Workpackage Title Integration and Verification Task No. 2.5. 3 Task Title Verification test of
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Continual learning of artificial intelligence systems based on bi-level optimization

Jan 1, 2023·
Ammar Shaker
,
Francesco Alesiani
,
Xiao He
· 0 min read
Cite
Type
Manuscript
Last updated on Jan 1, 2023
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© 2024 Francesco Alesiani. This work is licensed under CC BY NC ND 4.0

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