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Dominic BoutetIn the same vein as my <a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> thing, here's a paper that I've been reading and really enjoying. I decided to spend more time on it than I usually do when reading papers because I wanted to search for gaps in my knowledge, and I really don't regret that decision! I'm only at the 4th section at the moment and I find it very well written, especially in the framing of things. So far it's a great overview!"Neural Field Models: A mathematical overview and unifying framework" <a href="https://arxiv.org/abs/2103.10554v4" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2103.10554v4</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/MathematicalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MathematicalNeuroscience</a> <a href="https://neuromatch.social/tags/NeuralFieldModelling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NeuralFieldModelling</a> <a href="https://neuromatch.social/tags/Biophysical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Biophysical</a> <a href="https://neuromatch.social/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "JGAT: a joint spatio-temporal graph attention model for brain decoding" <a href="https://arxiv.org/abs/2306.05286" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2306.05286</a> <a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/Connectivity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Connectivity</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ML</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics" <a href="https://arxiv.org/abs/2305.18046" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2305.18046</a><a href="https://neuromatch.social/tags/MolecularDynamics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MolecularDynamics</a> <a href="https://neuromatch.social/tags/ComputationalModel" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalModel</a> <a href="https://neuromatch.social/tags/SurrogateModel" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#SurrogateModel</a> <a href="https://neuromatch.social/tags/TimeScale" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TimeScale</a> <a href="https://neuromatch.social/tags/Simulation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Simulation</a> <a href="https://neuromatch.social/tags/DiffusionModel" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DiffusionModel</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Transcranial stimulation of alpha oscillations modulates brain state dynamics in sustained attention" <a href="https://www.biorxiv.org/content/10.1101/2023.05.27.542583v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.05.27.542583v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/EEG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#EEG</a> <a href="https://neuromatch.social/tags/fMRI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#fMRI</a> <a href="https://neuromatch.social/tags/Oscillations" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Oscillations</a> <a href="https://neuromatch.social/tags/Attention" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Attention</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Learning low-dimensional dynamics from whole-brain data improves task capture" <a href="https://arxiv.org/abs/2305.14369" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2305.14369</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/NeuralODE" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NeuralODE</a> <a href="https://neuromatch.social/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a> <a href="https://neuromatch.social/tags/Cognition" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Cognition</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms" <a href="https://www.biorxiv.org/content/10.1101/2023.05.26.542448v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.05.26.542448v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/EEG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#EEG</a> <a href="https://neuromatch.social/tags/BetaBursts" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#BetaBursts</a> <a href="https://neuromatch.social/tags/Oscillations" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Oscillations</a> <a href="https://neuromatch.social/tags/WorkingMemory" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#WorkingMemory</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Distinct excitability of thalamocortical neurons correlates with the presence of cerebellar afferents" <a href="https://www.biorxiv.org/content/10.1101/2023.05.26.542536v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.05.26.542536v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Electrophysiology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Electrophysiology</a> <a href="https://neuromatch.social/tags/Cerebellum" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Cerebellum</a> <a href="https://neuromatch.social/tags/Thalamocortical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Thalamocortical</a> <a href="https://neuromatch.social/tags/MovementDisorders" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MovementDisorders</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Probabilistic Exponential Integrators" <a href="https://arxiv.org/abs/2305.14978" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2305.14978</a><a href="https://neuromatch.social/tags/NumericalModelling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NumericalModelling</a> <a href="https://neuromatch.social/tags/NumericalAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NumericalAnalysis</a> <a href="https://neuromatch.social/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a>

Dominic BoutetAfter a long break, new <a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation" <a href="https://arxiv.org/abs/2305.15208" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2305.15208</a> <a href="https://neuromatch.social/tags/BayesianInference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#BayesianInference</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/Modelling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Modelling</a> <a href="https://neuromatch.social/tags/SBI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#SBI</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Structural and neurophysiological alterations in Parkinson's disease are aligned with cortical neurochemical systems" <a href="https://www.medrxiv.org/content/10.1101/2023.04.04.23288137v1" rel="nofollow noopener noreferrer" target="_blank">https://www.medrxiv.org/content/10.1101/2023.04.04.23288137v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Multimodal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Multimodal</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/MEG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MEG</a> <a href="https://neuromatch.social/tags/Neurochemical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neurochemical</a> <a href="https://neuromatch.social/tags/Parkinsons" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Parkinsons</a> Incredible work, as always!

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> "Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias" <a href="https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/DynamicalModels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalModels</a> <a href="https://neuromatch.social/tags/DynamicalSystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DynamicalSystems</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/neurodegeneration" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#neurodegeneration</a> <a href="https://neuromatch.social/tags/TheVirtualBrain" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TheVirtualBrain</a>

Dominic Boutet<a href="https://neuromatch.social/tags/Arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Arxivfeed</a> :"Simulation-based inference for efficient identification of generative models in connectomics" <a href="https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/SimulationBasedInference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#SimulationBasedInference</a> <a href="https://neuromatch.social/tags/Inference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Inference</a> <a href="https://neuromatch.social/tags/Connectome" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Connectome</a> <a href="https://neuromatch.social/tags/Connectivity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Connectivity</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Neurophysiological signatures of cortical micro-architecture" <a href="https://www.biorxiv.org/content/10.1101/2023.01.23.525101v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.01.23.525101v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuro" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuro</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/Multimodal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Multimodal</a> <a href="https://neuromatch.social/tags/Neuroimaging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroimaging</a> <a href="https://neuromatch.social/tags/Neurophysiology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neurophysiology</a> Wonderful work!

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Neural network with optimal neuron activation functions based on additive Gaussian process regression" <a href="https://arxiv.org/abs/2301.05567" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2301.05567</a><a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DeepLearning</a> <a href="https://neuromatch.social/tags/GaussianProcess" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GaussianProcess</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Langevin algorithms for Markovian Neural Networks and Deep Stochastic control" <a href="https://arxiv.org/abs/2212.12018" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2212.12018</a><a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DeepLearning</a> <a href="https://neuromatch.social/tags/ControlTheory" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ControlTheory</a> <a href="https://neuromatch.social/tags/Optimization" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Optimization</a> <a href="https://neuromatch.social/tags/DifferentialEquations" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DifferentialEquations</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"How Occam's razor guides human decision-making" <a href="https://www.biorxiv.org/content/10.1101/2023.01.10.523479v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.01.10.523479v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuro" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuro</a> <a href="https://neuromatch.social/tags/Modelling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Modelling</a> <a href="https://neuromatch.social/tags/DecisionMaking" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DecisionMaking</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DeepLearning</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Mesoscopic modeling of hidden spiking neurons" <a href="https://arxiv.org/abs/2205.13493" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2205.13493</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuro" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuro</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/SpikingNeuralNetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#SpikingNeuralNetworks</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Seeking the Truth Beyond the Data. An Unsupervised Machine Learning Approach" <a href="https://arxiv.org/abs/2207.06949" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2207.06949</a><a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/UnsupervisedLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#UnsupervisedLearning</a> <a href="https://neuromatch.social/tags/Clustering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Clustering</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting" <a href="https://arxiv.org/abs/2301.02332" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/2301.02332</a><a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DeepLearning</a> <a href="https://neuromatch.social/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TimeSeries</a> <a href="https://neuromatch.social/tags/Forecasting" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Forecasting</a> <a href="https://neuromatch.social/tags/NeuralNetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NeuralNetworks</a>

Dominic Boutet<a href="https://neuromatch.social/tags/arxivfeed" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#arxivfeed</a> :"Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks" <a href="https://www.biorxiv.org/content/10.1101/2023.01.05.522909v1" rel="nofollow noopener noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2023.01.05.522909v1</a><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/Neuro" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Neuro</a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ComputationalNeuroscience</a> <a href="https://neuromatch.social/tags/Vision" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Vision</a> <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#MachineLearning</a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DeepLearning</a> <a href="https://neuromatch.social/tags/ConvolutionalNeuralNetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ConvolutionalNeuralNetworks</a>

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