36 citations · 59 across the 5 of their papers we have counts for
6 papers
Deep Learning: Our Miraculous Year 1990-1991
Juergen Schmidhuber
The Deep Learning Artificial Neural Networks (NNs) of our team have revolutionised Machine Learning & AI. Many of the basic ideas behind this revolution were published within the 1…
Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions
Juergen Schmidhuber
We transform reinforcement learning (RL) into a form of supervised learning (SL) by turning traditional RL on its head, calling this Upside Down RL (UDRL). Standard RL predicts rew…
Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)
Juergen Schmidhuber
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One ne…
Investigations on End-to-End Audiovisual Fusion
Michael Wand, Ngoc Thang Vu, Juergen Schmidhuber
Audiovisual speech recognition (AVSR) is a method to alleviate the adverse effect of noise in the acoustic signal. Leveraging recent developments in deep neural network-based speec…
Hindsight policy gradients
Paulo Rauber, Avinash Ummadisingu, Filipe Mutz +1
A reinforcement learning agent that needs to pursue different goals across episodes requires a goal-conditional policy. In addition to their potential to generalize desirable behav…
A Linear Time Natural Evolution Strategy for Non-Separable Functions
Yi Sun, Faustino Gomez, Tom Schaul +1
We present a novel Natural Evolution Strategy (NES) variant, the Rank-One NES (R1-NES), which uses a low rank approximation of the search distribution covariance matrix. The algori…