PFN福田圭祐による東大大学院「融合情報学特別講義Ⅲ」(2022年10月19日)の講義資料です。
・Introduction to Preferred Networks
・Our developments to date
・Our research & platform
・Simulation ✕ AI
ConvMixer is a simple CNN-based model that achieves state-of-the-art results on ImageNet classification. It divides the input image into patches and embeds them into high-dimensional vectors, similar to ViT. However, unlike ViT, it does not use attention but instead applies simple convolutional layers between the patch embedding and classification layers. Experiments show that despite its simplicity, ConvMixer outperforms more complex models like ResNet, ViT, and MLP-Mixer on ImageNet, demonstrating that patch embeddings may be as important as attention mechanisms for vision tasks.
PFN福田圭祐による東大大学院「融合情報学特別講義Ⅲ」(2022年10月19日)の講義資料です。
・Introduction to Preferred Networks
・Our developments to date
・Our research & platform
・Simulation ✕ AI
ConvMixer is a simple CNN-based model that achieves state-of-the-art results on ImageNet classification. It divides the input image into patches and embeds them into high-dimensional vectors, similar to ViT. However, unlike ViT, it does not use attention but instead applies simple convolutional layers between the patch embedding and classification layers. Experiments show that despite its simplicity, ConvMixer outperforms more complex models like ResNet, ViT, and MLP-Mixer on ImageNet, demonstrating that patch embeddings may be as important as attention mechanisms for vision tasks.
Full stack component of software and middleware for quantum machineYuichiro MInato
MDR Inc. is a Japanese quantum computing company that develops full-stack quantum computing software and middleware. It was founded in 2008 and has 15 employees including software engineers, finance specialists, and an advisor. MDR provides an open-source SDK for quantum application development, works with clients in various industries to develop quantum machine learning and optimization applications, and partners with hardware providers and research institutions.
This document discusses quantum computing business in the Japanese market. It introduces MDR Inc., a Japanese quantum computing startup founded in 2008. MDR develops full-stack quantum computing, from software to hardware, and works with over 20 clients in industries like banking, automotive, materials and more. Some applications discussed include quantum simulation, optimization, and machine learning. The document also provides an overview of the quantum computing developer community and ecosystem in Japan.
This document provides an overview of quantum computing, including:
1. There are two types of quantum computers - universal gate models that change gates over time to calculate circuits, and quantum annealers that set parameters first and obtain an answer.
2. Existing quantum computers are limited by noise and errors and cannot directly implement logical circuits, though variational algorithms like VQE are widely used.
3. Quantum hardware requires cryostats for cooling and controlling superconducting qubits, while software includes libraries for converting problems to the Ising model solved by annealers.