A Programmable Topological Photonic Chip

A Programmable Topological Photonic Chip

Physics, Optics, Quantum Physics, Information Science, Computer Science, Semiconductors and Information Devices,
topological phases   photonic chip   silicon photonics   microresonators   dynamic topological phase transitions  

Research Progress on Programmable Topological Photonic Chips Research Background In recent years, topological insulators (TI) have garnered significant attention in the physics community due to their rich physical mechanisms and the potential applications of topological boundary modes, leading to rapid development in this field. Since the discovery...

Advanced Optimal Tracking Integrating a Neural Critic Technique for Asymmetric Constrained Zero-Sum Games

Mathematics, Information Science, Automation, Artificial Intelligence,
neural networks   adaptive dynamic programming   asymmetric constraints   zero-sum games   optimal tracking control  

Academic Report: Advanced Optimal Tracking Integrating Neural Critic Technique for Asymmetric Constrained Zero-Sum Games Background and Research Problem In the field of modern control, game theory is the mathematical model that studies the competition and cooperation between intelligent decision-makers, involving an interaction decision problem wit...

An Invisible, Robust Protection Method for DNN-Generated Content

Information Science, Artificial Intelligence,
deep neural networks   invisible perturbation   protection technique   robustness   generated content   image encoding   social media  

Invisible and Robust Protection Method for Content Generated by Deep Neural Networks Academic Background In recent years, with the revolutionary development and widespread application of deep learning models in engineering applications, phenomenon-level applications such as ChatGPT and DALL⋅E 2 have emerged, profoundly impacting people’s daily live...

m𝟐ixkg: Mixing for harder negative samples in knowledge graph

Information Science, Computer Science, Artificial Intelligence,
knowledge graph   negative sampling   embedding   mixing operation   entities  

Academic Report Background A Knowledge Graph (KG) is structured data that records information about entities and relationships, widely used in question-answering systems, information retrieval, machine reading, and other fields. Knowledge Graph Embedding (KGE) technology maps entities and relationships in the graph into a low-dimensional dense vect...

Exploring Adaptive Inter-Sample Relationship in Data-Free Knowledge Distillation

Information Science, Artificial Intelligence,
data-free knowledge distillation   unsupervised representation learning   knowledge distillation   adaptive methods   inter-sample relationship  

In recent years, applications such as privacy protection and large-scale data transmission have posed significant challenges to the inaccessibility of data. Researchers have proposed Data-Free Knowledge Distillation (DFKD) methods to address these issues. Knowledge Distillation (KD) is a method for training a lightweight model (student model) to le...

Modeling Bellman-Error with Logistic Distribution with Applications in Reinforcement Learning

Mathematics, Information Science, Artificial Intelligence,
reinforcement learning   logistic distribution   reward scaling   bellman error  

Background and Research Objectives Reinforcement Learning (RL) has recently become a dynamic and transformative field within artificial intelligence, aiming to maximize cumulative rewards through the interaction between agents and the environment. However, the application of RL faces challenges in optimizing the Bellman Error. This error is particu...