3 citations · 3 across the 3 of their papers we have counts for
6 papers
Credit-cognisant reinforcement learning for multi-agent cooperation
F. Bredell, H. A. Engelbrecht, J. C. Schoeman
Traditional multi-agent reinforcement learning (MARL) algorithms, such as independent Q-learning, struggle when presented with partially observable scenarios, and where agents are…
Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language
Kevin Eloff, Herman A. Engelbrecht
Communication between agents in collaborative multi-agent settings is in general implicit or a direct data stream. This paper considers text-based natural language as a novel form…
Unsupervised feature learning for speech using correspondence and Siamese networks
Petri-Johan Last, Herman A. Engelbrecht, Herman Kamper
In zero-resource settings where transcribed speech audio is unavailable, unsupervised feature learning is essential for downstream speech processing tasks. Here we compare two rece…
Deep motion estimation for parallel inter-frame prediction in video compression
André Nortje, Herman A. Engelbrecht, Herman Kamper
Standard video codecs rely on optical flow to guide inter-frame prediction: pixels from reference frames are moved via motion vectors to predict target video frames. We propose to…
BINet: a binary inpainting network for deep patch-based image compression
André Nortje, Willie Brink, Herman A. Engelbrecht +1
Recent deep learning models outperform standard lossy image compression codecs. However, applying these models on a patch-by-patch basis requires that each image patch be encoded a…
Multimodal One-Shot Learning of Speech and Images
Ryan Eloff, Herman A. Engelbrecht, Herman Kamper
Imagine a robot is shown new concepts visually together with spoken tags, e.g. "milk", "eggs", "butter". After seeing one paired audio-visual example per class, it is shown a new s…