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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 1 month ago
that diffusion models are a fundamental divergence from traditional deep learning paradigms. This suggests that existing generalisation theories are insufficient and highlights the need for a bespoke, algorithm
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of the key components of the project is the apply machine learning algorithms on video data to extract human behavioural patterns (from egocentric and exocentric views). For that purpose, we are looking
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with CamDragon Co. Ltd, a Cambridge-based SME offering engineering consultancy and STEM education
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and implementation of parton-shower algorithms and their matching to higher-order pertubative computations in Quantum Chromodynamics. Additionally the analyses of the results in the context of the LHC
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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, probabalistic algorithms Noam Lifshitz Extremal combinatorics, additive combinatorics, analysis of boolean functions Elon Lindenstrauss Homogeneous dynamics, ergodic theory, number theory, additive
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on experience and qualifications). More information about this position is available on https://uol.de/en/job/research-associate-foundation-models-for-hearing-aid-processing-819 The position is embedded within
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of precipitation and temperature over Morocco. Key Responsibilities: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation
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approach development for rescaling the temporal and spatial resolution of satellite images to be used in prediction algorithm and software development Develop Research Report, Conference Presentations
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Pest Management in The Western U.S.' (https://ai4sa.ucr.edu/ ). The overall goal of this project is to develop advanced tools for early stress (abiotic and biotic) detection and decision support for crop