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AMADEUS_AI
⏲ 93 sec ✓ 28-Feb-2020
TOMITA - Recurrent Neural Network
⏲ 93 sec ✓ 28-Feb-2017
Document Embedding Enhanced Event Detection with Hierarchical and Supervised Attention
⏲ 5 min 98 sec ✓ 20-Aug-2018
RNN
⏲ 4 min 34 sec ✓ 03-Jan-2019
Chi Nhan Nguyen: Bidirectional RNN zur Extraktion relevanter Felder in Rechnungen
⏲ 16 min 1 sec ✓ 19-Jun-2018
RNN
⏲ 25 min 36 sec ✓ 12-Dec-2022
Marc Engenhart »#SU – a journey into sound (Symphonia Universalis)« | Rise of AI conference 2019
⏲ 16 min 84 sec ✓ 03-Jul-2019
A Magical AI Angle
⏲ 1 min 92 sec ✓ 29-Apr-2020
Module 6_RNN4_demo_Time Series Exercise
⏲ 6 min 65 sec ✓ 19-Nov-2018
Deconstructing Deep Learning
⏲ 26 min 45 sec ✓ 08-Oct-2019
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_amadeus-ai.webp "Could an Artificial Intelligence bring minds from the past to the present?nCould them start writing music through it again?nCould they be writing it eternally?nAmadeus ai is an artistic installation which, with the use of artificial intelligence, resurrects one of the most creative minds in the human history, Mozart. Our piano with motorized keys, analysing the composer's logic, reproduces it’s own musical notes generated real time.nThe installation consists of two side projection screens that")
_tomita-recurrent-neural-network.webp "This was a hack I worked on at Kano, it's a char-rnn based neural network trained on 10,000 code based artworks created using https://art.kano.mennart.kano.me teaches kids how to code, their creations taught a computer how to code.nnhttps://github.com/neue/tomita/nnMusic: Freaky Eyes - Oneohtrix Point Never")
_document-embedding-enhanced-event-detection-with-hierarchical-and-supervised-attention.webp "Document-level information is very important for event detection even at sentence level. In this paper, we propose a novel Document Embedding Enhanced Bi-RNN model, called DEEB-RNN, to detect events in sentences. This model first learns event detection oriented embeddings of documents through a hierarchical and supervised attention based RNN, which pays word-level attention to event triggers and sentence-level attention to those sentences containing events. It then uses the learned document embe")
_rnn.webp "RNN from rnn")
_chi-nhan-nguyen-bidirectional-rnn-zur-extraktion-relevanter-felder-in-rechnungen.webp "Die automatische Extraktion relevanter Daten in Rechnungsdokumenten kann als wertvolle Grundlage für viele Dienstleistungen in der Finanz- und Buchhaltungsbranche dienen. Die Anwendung von Deep Learning für diesen Zweck ist vor allem durch die enorme Vielzahl an unterschiedlichen Layouts auf dem Markt motiviert. nnIch möchte die grundlegende Architektur des")
_rnn.webp "Default description")
_marc-engenhart-su-a-journey-into-sound-symphonia-universalis-124-rise-of-ai-conference-2019.webp "Marc Engenhart »#SU – Symphonia Universalis«, a journey into sound« Speech @ Rise Of AI Conference 2019 in Berlin, AI Evolution StagennThe SU is a man-machine installation, model for augmented transformative creatitiy through music.nnSU is still searching for investors/patrons to realise additional functionalities. You are invited to contact mail(at)engenhart.com to join the project.nnSound-Intro ends at 2:15 min. German version and subtitles to be available soon. nnAll rights reserved by M")
_a-magical-ai-angle.webp "Demonstrating prototype for an installation piece. An AI oracle is becoming increasingly confused about the expectations that artificial intelligence should come up to. Done with MaxMSP and Arduino. Predictions are generated with a RNN in TensorFlow.")
_module-6-rnn4-demo-time-series-exercise.webp "Module 6_RNN4_demo_Time Series Exercise from rnn")
_deconstructing-deep-learning.webp "Attend this session for a mathematics and jargon free introduction to Deep Learning and Artificial Neural Networks!nnThe talk is split into three sections as follows:nn1. I’ll start by outlining the general principles and theory behind Deep Learning.nn2. Next up I’ll explain the inner workings of Convolutional Neural Networks (CNNs) and show how these can be utilised for Image Processing,nn3. Finally I’ll give insight into how Recurrent Neural Networks (RNN) can be used for Natural Languag")
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