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Found 10 papers, 2 papers with code
Leveraging Industry 4.0 -- Deep Learning, Surrogate Model and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System
After that, a detailed overview of uncertainties, uncertainty quantification frameworks, and specifics of uncertainty quantification methodologies for a surrogate model linked to a digital twin is presented.
Digital Twin and Artificial Intelligence Incorporated With Surrogate Modeling for Hybrid and Sustainable Energy Systems
Backed by Artificial Intelligence, a surrogate model can present highly accurate results with a significant reduction in computation time than computer simulation of actual models.
Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications
This chapter also focuses on the application of machine learning and artificial intelligence in the design optimization, control, and monitoring of small modular reactors.
LIP: Lightweight Intelligent Preprocessor for meaningful text-to-speech
In this work, we aim to introduce a lightweight intelligent preprocessor (LIP) that can enhance the readability of a message before being passed downstream to existing TTS systems.
A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing
We propose a Deep Reinforcement Learning (Deep RL) algorithm for solving the online 3D bin packing problem for an arbitrary number of bins and any bin size.
SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning
We propose a generic reward shaping approach for improving the rate of convergence in reinforcement learning (RL), called Self Improvement Based REwards, or SIBRE.
Accelerating Training in Pommerman with Imitation and Reinforcement Learning
Our methodology involves training an agent initially through imitation learning on a noisy expert policy, followed by a proximal-policy optimization (PPO) reinforcement learning algorithm.
MAPEL: Multi-Agent Pursuer-Evader Learning using Situation Report
We present a detailed analysis of how these two cooperation methods perform when the number of agents in the game are increased.
DyPerm: Maximizing Permanence for Dynamic Community Detection
In this paper, we propose DyPerm, the first dynamic community detection method which optimizes a novel community scoring metric, called permanence.
Social and Information Networks Physics and Society
Indian Regional Movie Dataset for Recommender Systems
It consists of movies belonging to 18 different Indian regional languages and metadata of users with varying demographics.
