Paper: Temporal Knowledge Graph Reasoning with Historical Contrastive Learning Temporal Knowledge GraphKnowledge Graphs (KGs), as a collection of human knowledge, have shown great prospects in natural language processing, recommendation systems and information retrieval. The tra 2022-12-03 technology machine learning Python knowledge graph
DeepScience: Forecasting Trends of the Science of Science IntroductionIn this repo, we choose the domain of COVID-19 and deep learning to predict the trends of the science of science. We use the information of papers and fields from Acemap. It is worth noti 2022-03-19 technology machine learning
Python Implementation of Contrastive Learning IntroductionContrastive learning is a self-supervised learning method to learn representations by contrasting positive and negative examples. For self-supervised contrastive learning, the next equatio 2022-01-13 technology machine learning Python
Image Generation with Generative Adversarial Networks (GAN) IntroductionIn this article, I implemented some variants of DCGAN[1], which is one of the generative adversarial networks. The DCGAN model has replaced the fully connected layer with the global poolin 2021-07-09 technology machine learning Python
Critique: DNNGuard: An Elastic Heterogeneous DNN Accelerator Architecture against Adversarial Attacks Paper: Wang, Xingbin, et al. “Dnnguard: An elastic heterogeneous dnn accelerator architecture against adversarial attacks.” Proceedings of the Twenty-Fifth International Conference on Architectural S 2021-04-12 technology computer architecture paper
Critique: Think fast: a tensor streaming processor (TSP) for accelerating deep learning workloads Paper: Abts, Dennis, et al. “Think fast: a tensor streaming processor (TSP) for accelerating deep learning workloads.” 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA 2021-02-03 technology computer architecture paper
von Neumann Graph Entropy: Python Implementation IntroductionThe von Neumann graph entropy (VNGE) facilitates measurement of information divergence and distance between graphs in a graph sequence. Given an undirected graph G=(V, E, A), where A is t 2021-01-25 technology machine learning Python
Critique: Accelerating Attention Mechanisms in Neural Networks with Approximation Paper: Ham, Tae Jun, et al. “A^ 3: Accelerating Attention Mechanisms in Neural Networks with Approximation.” 2020 IEEE International Symposium on High Performance Computer Architecture (HPCA). IEEE, 2021-01-20 technology computer architecture paper
Critique: Why GPUs are slow at executing NFAs and how to make them faster. Paper: Liu, Hongyuan, Sreepathi Pai, and Adwait Jog. “Why GPUs are slow at executing NFAs and how to make them faster.” Proceedings of the Twenty-Fifth International Conference on Architectural Suppo 2021-01-20 technology computer architecture paper
Defend the truth: seeing is not believing anymore DeepFakeImagine if someone replaces the character in a certain video with your face image just for fun, what would you think? This is what DeepFake is doing. Its function is to combine and superimpose 2021-01-20 ideas ideas
