Biologically-plausible Training
5 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Biologically-plausible Training
Most implemented papers
Biologically-plausible learning algorithms can scale to large datasets
willwx/sign-symmetry
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ICLR 2019
These results complement the study by Bartunov et al. (2018), and establish a new benchmark for future biologically plausible learning algorithms on more difficult datasets and more complex architectures.
Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling
In sequence learning tasks such as language modelling, Recurrent Neural Networks must learn relationships between input features separated by time.
Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks
We develop biologically plausible training mechanisms for self-supervised learning (SSL) in deep networks.
Feed-Forward Optimization With Delayed Feedback for Neural Networks
Backpropagation has long been criticized for being biologically implausible, relying on concepts that are not viable in natural learning processes.
Connectivity-Inspired Network for Context-Aware Recognition
We inform the AI practitioner about the human visual system with an extensive literature review; we propose a novel biologically motivated neural network for image classification; and, finally, we present a new plug-and-play module to model context awareness.
