310 citations · 1.9k across the 36 of their papers we have counts for
11 papers · 1 filter
Unraveling the geometry of visual relational reasoning
Jiaqi Shang, Gabriel Kreiman, Haim Sompolinsky
Humans readily generalize abstract relations, such as recognizing "constant" in shape or color, whereas neural networks struggle, limiting their flexible reasoning. To investigate…
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds
Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy +4
Recently, growth in our understanding of the computations performed in both biological and artificial neural networks has largely been driven by either low-level mechanistic studie…
A theory of learning with constrained weight-distribution
Weishun Zhong, Ben Sorscher, Daniel D Lee +1
A central question in computational neuroscience is how structure determines function in neural networks. The emerging high-quality large-scale connectomic datasets raise the quest…
Temporal support vectors for spiking neuronal networks
Ran Rubin, Haim Sompolinsky
When neural circuits learn to perform a task, it is often the case that there are many sets of synaptic connections that are consistent with the task. However, only a small number…
Optimal quadratic binding for relational reasoning in vector symbolic neural architectures
Naoki Hiratani, Haim Sompolinsky
Binding operation is fundamental to many cognitive processes, such as cognitive map formation, relational reasoning, and language comprehension. In these processes, two different m…
Macroscopic Fluctuations Emerge in Balanced Networks with Incomplete Recurrent Alignment
Itamar Daniel Landau, Haim Sompolinsky
Networks of strongly-coupled neurons with random connectivity exhibit chaotic, asynchronous fluctuations. In previous work, we showed that when endowed with an additional low-rank…