8 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
Unsupervised Musical Object Discovery from Audio
Joonsu Gha, Vincent Herrmann, Benjamin Grewe +2
Current object-centric learning models such as the popular SlotAttention architecture allow for unsupervised visual scene decomposition. Our novel MusicSlots method adapts SlotAtte…
Exploring the Promise and Limits of Real-Time Recurrent Learning
Kazuki Irie, Anand Gopalakrishnan, Jürgen Schmidhuber
Real-time recurrent learning (RTRL) for sequence-processing recurrent neural networks (RNNs) offers certain conceptual advantages over backpropagation through time (BPTT). RTRL req…
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
Contrastive Training of Complex-Valued Autoencoders for Object Discovery
Aleksandar Stanić, Anand Gopalakrishnan, Kazuki Irie +1
Current state-of-the-art object-centric models use slots and attention-based routing for binding. However, this class of models has several conceptual limitations: the number of sl…