Skip to content Zenke Lab Computational Neuroscience at the FMI Selected talks from the lab Research Funding Spiking Heidelberg Digits and Spiking Speech Commands Auryn Spiking Network Simulator LaTeX rebuttal/response to reviewers template Great free text books Fluctuation-driven initialization for spiking neural network training June 23, 2022October 6, 2022 fzenke Surrogate gradients are a great tool for training spiking neural networks in computational neuroscience and neuromorphic engineering, but what

In neural networks, a polytope is a region of the input space that captures a particular category or concept. Polytopes are a proposed fundamental building block of neural networks, and the perspective that views them this way is known as the ‘<strong>polytope lens</strong>’. In neural networks that use what is arguably the most popular set of r

In neural networks, a polytope is a region of the input space that captures a particular category or concept. Polytopes are a proposed fundamental building block of neural networks, and the perspective that views them this way is known as the ‘<strong>polytope lens</strong>’. In neural networks that use what is arguably the most popular set of r

NeurIPS 2020 Mutual exclusivity as a challenge for deep neural networks Review 1 Summary and Contributions: People are biased to assume that each object has a single label, which is called the “mutual exclusivity” bias. This aids inference for novel objects and in other situations. The paper examines whether single hidden layer feedforward and seq2seq neural networks have a mutual exclusivity bias. First, they examine how different variants predict the label of a novel object after learning several

# ModelStar: Reachability Analysis-based Safety Verification of Neural Networks Against Model Perturbations ## Article Sidebar Published: Apr 7, 2026 Keywords: neural networks, qualitative reasoning, uncertainty ## Main Article Content Muhammad Usama Zubair Taylor T. Johnson Vanderbilt University, Nashville, TN 37212 USA Kanad Basu University of Texas at Dallas, Richardson, TX 75080, USA Waseem Abbas University of Texas at Dallas, Richardson, TX 75080, USA ## Abstract The widespread adoption o

Jump to content Main menu Main menu move to sidebar hide Navigation Contribute Search Search Appearance Personal tools Contents move to sidebar hide (Top) 1 History Toggle History subsection 1.1 Before modern 1.2 Modern 2 Configurations Toggle Configurations subsection 2.1 Standard 2.2 Stacked RNN 2.3 Bidirectional 2.4 Encoder-decoder 2.5 PixelRNN 3 Architectures Toggle Architectures subsection 3.1 Fully recurrent 3.2 Hopfield 3.3 Elman networks and Jordan networks 3.4 Long short-term memory 3.5 Gated recur

Part Of: Neuroanatomy sequenceContent Summary: 2200 words, 22 min read Four Cortical Networks Cognitive neuroscience typically employs fMRI scans under a carefully crafted task structure. Such research localized various task functions to different neural structures (cortical areas). For example, these studies produced evidence suggesting that the hippocampus is the seat of autobiographical memory. In the

Skip to content Commercial Intelligence systems that know and understand and think and learn Posted on June 28, 2019June 28, 2019 by [email protected] Neural Logic Machines This is an important paper in the development of neural reasoning capabilities which should reduce the brittleness of purely symbolic approaches: Neural Logic Machine The potential reasoning capabilities, such as with regard to multi-step inference, as in problem solving and theorem proving, are most interesting, but there are important c

Psychology studies have demonstrated that by the age of 4–5, young children have developed intricate visual models of the world around them. These internal visual models allow them to outperform advanced computer vision techniques ...

CSP Test --> Main Navigation ICML My Stuff Login Select Year: (2026) 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2002 1996 IMLS Archives Oral Thu, Jul 9, 2026 • 12:45 AM – 1:00 AM PDT ASEM BALLROOM 201-203 Which Algorithms Can Graph Neural Networks Learn? Solveig Wittig ⋅ Antonis Vasileiou ⋅ Robert R. Nerem ⋅ Timo Stoll ⋅ Floris Geerts ⋅ Yusu Wang ⋅ Christopher Morris Poster presentation: Poster Session 8 [ OpenReview