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Opening & Group Picture 08.0 a.m. - 09.00 a.m.
Challenges and Opportunities for Generative AI in Africa
Challenges and Opportunities for Generative AI in Africa
Jacki O'Neill | Microsoft Africa Research Institute (MARI), Nairobi County | 09.00 - 09.45
A physics-informed neural network framework for modeling obstacle-related equations
A physics-informed neural network framework for modeling obstacle-related equations
Hamid Elbahja | AIMS RIC | 09.45 - 10.30
Physics-informed neural networks for Timoshenko system with Thermoelasticity
Physics-informed neural networks for Timoshenko system with Thermoelasticity
Sabrine Chebbi | University of Tübingen & AIMS South Africa | 10.45 - 11.30
Delving into Scientific Machine Learning: Solving Partial Differential Equations and related Parameter Identification Problems with TorchPhysics
Delving into Scientific Machine Learning: Solving Partial Differential Equations and related Parameter Identification Problems with TorchPhysics
Derick Tanyu | Universität Bremen, Germany | 11.30 - 12.15
Geometric and Algebraic Aspects of Knowledge Graph Embedding
Geometric and Algebraic Aspects of Knowledge Graph Embedding
Kossi Amouzouvi | TU Dresden, Germany | 13.30 - 14.15
Computer Vision in Practice: Off-the-shelf or Own Shelf?
Computer Vision in Practice: Off-the-shelf or Own Shelf?
Anna Bosman | University of Pretoria, South Africa | 14.15 .- 15.00
Data Analysis and Forecasting of COVID-19 Within African Regions
Data Analysis and Forecasting of COVID-19 Within African Regions
Louis Fendji | University of Ngaoundéré, Cameroon | 15.00 - 15.45
Interpolating between MCMC sampling and variational inference with infinite stochastic mixtures
Interpolating between MCMC sampling and variational inference with infinite stochastic mixtures
Richard Lange | RIT, New York | 16.05 - 16.50
Image-based, AI-assisted detection of early stress response in plant leaves
Image-based, AI-assisted detection of early stress response in plant leaves
Alice Malivert | Imperial College London, UK | 16.50 - 17.35
Security and Robustness of Machine Learning under Vulnerable Cyberinfrastructure and Varying Data Quality
Security and Robustness of Machine Learning under Vulnerable Cyberinfrastructure and Varying Data Quality
Sergei Chuprov | RIT, New York | 17.35 - 18.20
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