805 citations · 808 across the 3 of their papers we have counts for
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cs.LG2026
Decomposing multimodal embedding spaces with group-sparse autoencoders
Chiraag Kaushik, Davis Barch, Andrea Fanelli
The Linear Representation Hypothesis asserts that the embeddings learned by neural networks can be understood as linear combinations of features corresponding to high-level concept…
cs.LG2018★ 3 cited
Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing
Jeffrey L Mckinstry, Davis R. Barch, Deepika Bablani +5
Low precision networks in the reinforcement learning (RL) setting are relatively unexplored because of the limitations of binary activations for function approximation. Here, in th…