#arxivfeed — Public Fediverse posts

In the same vein as my #arxivfeed 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"
https://arxiv.org/abs/2103.10554v4

#Neuroscience #ComputationalNeuroscience #MathematicalNeuroscience #NeuralFieldModelling #Biophysical #DynamicalSystems

#arxivfeed

"Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics"
https://arxiv.org/abs/2305.18046

#MolecularDynamics #ComputationalModel #SurrogateModel #TimeScale #Simulation #DiffusionModel

#arxivfeed

"Learning low-dimensional dynamics from whole-brain data improves task capture"
https://arxiv.org/abs/2305.14369

#Neuroscience #ComputationalNeuroscience #MachineLearning #Neuroimaging #NeuralODE #DynamicalSystems #Cognition

#arxivfeed

"Distinct excitability of thalamocortical neurons correlates with the presence of cerebellar afferents"
https://www.biorxiv.org/content/10.1101/2023.05.26.542536v1

#Neuroscience #Electrophysiology #Cerebellum #Thalamocortical #MovementDisorders

After a long break, new #arxivfeed

"Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation"
https://arxiv.org/abs/2305.15208

#BayesianInference #MachineLearning #Modelling #SBI #ComputationalNeuroscience

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#arxivfeed :

"Neural network with optimal neuron activation functions based on additive Gaussian process regression"
https://arxiv.org/abs/2301.05567

#MachineLearning #DeepLearning #GaussianProcess

#arxivfeed :

"Seeking the Truth Beyond the Data. An Unsupervised Machine Learning Approach"
https://arxiv.org/abs/2207.06949

#MachineLearning #UnsupervisedLearning #Clustering

#arxivfeed :

"Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks"
https://www.biorxiv.org/content/10.1101/2023.01.05.522909v1

#Neuroscience #Neuro #ComputationalNeuroscience #Vision #MachineLearning #DeepLearning #ConvolutionalNeuralNetworks

#arxivfeed :

"Dynamic Bayesian Learning and Calibration of Spatiotemporal Mechanistic Systems"
https://arxiv.org/abs/2208.06528

#DynamicalSystems #ModelCalibration #Bayesian #ParameterEstimation #GaussianProcess

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions"
https://arxiv.org/abs/2206.05183

#MachineLearning #DeepLearning #Variational #Autoencoder #DynamicalSystems

#arxivfeed :

"Auto-Encoding Variational Bayes"
https://arxiv.org/abs/1312.6114

#MachineLearning #VariationalBayes #Bayesian #Inference #ProbabilisticModel #AutoEncoder #DeepLearning

#arxivfeed :

"NIT: an open-source tool for information theoretic analysis of neural population data"
https://www.biorxiv.org/content/10.1101/2022.12.11.519966v1

#Neuroscience #Neuro #Brain #DataAnalysis #InformationTheory #TwoPhoton #CalciumImaging

#arxivfeed :

"Biologically plausible unsupervised learning in neural networks with sparse and asymmetric connectivity"
https://www.biorxiv.org/content/10.1101/2022.11.30.518534v1

#MachineLearning #UnsupervisedLearning #NeuralNetworks #NeuroAI #BoltzmannMachines

#arxivfeed :

"A biology-inspired recurrent oscillator network for computations in high-dimensional state space"
https://www.biorxiv.org/content/10.1101/2022.11.29.518360v1

#MachineLearning #DeepLearning #RecurrentNeuralNetwork #NeuroAI #Neuroscience #DynamicalSystems #UnsupervisedLearning #HebbainLearning

#arxivfeed :

"A Topological Deep Learning Framework for Neural Spike Decoding"
https://arxiv.org/abs/2212.05037

#Neuroscience #Neuro #Brain #MachineLearning #DeepLearning #FeatureExtraction #SpikeTrains #GridCells #HeadDirectionCells

#arxivfeed :

"A Topological Deep Learning Framework for Neural Spike Decoding"
https://arxiv.org/abs/2212.05037

#Neuroscience #Neuro #Brain #MachineLearning #DeepLearning #FeatureExtraction #SpikeTrains #GridCells #HeadDirectionCells

#arxivfeed :

"A Topological Deep Learning Framework for Neural Spike Decoding"
https://arxiv.org/abs/2212.05037

#Neuroscience #Neuro #Brain #MachineLearning #DeepLearning #FeatureExtraction #SpikeTrains #GridCells #HeadDirectionCells

#arxivfeed :

"A Topological Deep Learning Framework for Neural Spike Decoding"
https://arxiv.org/abs/2212.05037

#Neuroscience #Neuro #Brain #MachineLearning #DeepLearning #FeatureExtraction #SpikeTrains #GridCells #HeadDirectionCells

#arxivfeed :

"A Topological Deep Learning Framework for Neural Spike Decoding"
https://arxiv.org/abs/2212.05037

#Neuroscience #Neuro #Brain #MachineLearning #DeepLearning #FeatureExtraction #SpikeTrains #GridCells #HeadDirectionCells

#arxivfeed :

"Get a new perspective on EEG: Convolutional neural network encoders for parametric t-SNE."
https://www.biorxiv.org/content/10.1101/2022.12.08.519691v1

#Neuroscience #Neuro #Brain #Neuroimaging #EEG #DimensionalityReduction #tSNE #DeepLearning #NeuralNetworks

#arxivfeed :

"The mechanics underpinning non-deterministic computation in cortical neural networks"
https://www.biorxiv.org/content/10.1101/2022.12.03.518983v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #Computations

#arxivfeed :

"Random electrical noise drives non-deterministic computation in cortical neural networks"
https://www.biorxiv.org/content/10.1101/2022.12.03.518981v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #Computations

#arxivfeed :

"Modeling electron interference at the neuronal membrane yields a holographic projection of representative information content"
https://www.biorxiv.org/content/10.1101/2022.12.03.518989v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #Computations

#arxivfeed :

"A thermodynamical model of non-deterministic computation in cortical neural networks"
https://www.biorxiv.org/content/10.1101/2022.12.03.518978v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #Computations #ProbabilisticCoding #Thermodynamic #Hamiltonian

#arxivfeed :

"Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks"
https://www.biorxiv.org/content/10.1101/2022.12.02.518809v1

#Neurocience #Neuro #Brain #DynamicalSystems #WholeBrainModel #Simulations #Neuroimaging

#arxivfeed :

"Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling"
https://www.biorxiv.org/content/10.1101/2022.11.29.518317v1

#Neuroscience #Neuro #Brain #Neurophysiology #Biophysics #Neuron #NeuronModel #Simulation #ActionPotential

#arxivfeed :

"Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling"
https://www.biorxiv.org/content/10.1101/2022.11.29.518317v1

#Neuroscience #Neuro #Brain #Neurophysiology #Biophysics #Neuron #NeuronModel #Simulation #ActionPotential

#arxivfeed :

"Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling"
https://www.biorxiv.org/content/10.1101/2022.11.29.518317v1

#Neuroscience #Neuro #Brain #Neurophysiology #Biophysics #Neuron #NeuronModel #Simulation #ActionPotential

#arxivfeed :

"Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling"
https://www.biorxiv.org/content/10.1101/2022.11.29.518317v1

#Neuroscience #Neuro #Brain #Neurophysiology #Biophysics #Neuron #NeuronModel #Simulation #ActionPotential

#arxivfeed :

"Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling"
https://www.biorxiv.org/content/10.1101/2022.11.29.518317v1

#Neuroscience #Neuro #Brain #Neurophysiology #Biophysics #Neuron #NeuronModel #Simulation #ActionPotential

#arxivfeed :

"Temporal characteristics of gamma rhythm constrain properties of noise in an inhibition-stabilized network model"
https://www.biorxiv.org/content/10.1101/2022.11.23.517655v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #VisualSystem #DynamicalSystems

#arxivfeed :

"Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings"
https://www.biorxiv.org/content/10.1101/2022.11.17.516914v1

#Neuroscience #Neuro #Brain #NeuralNetwork #RNN #Connectivity #StructuralConnectivity #FunctionalConnectivity

#arxivfeed :

"Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings"
https://www.biorxiv.org/content/10.1101/2022.11.17.516914v1

#Neuroscience #Neuro #Brain #NeuralNetwork #RNN #Connectivity #StructuralConnectivity #FunctionalConnectivity

#arxivfeed :

"Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings"
https://www.biorxiv.org/content/10.1101/2022.11.17.516914v1

#Neuroscience #Neuro #Brain #NeuralNetwork #RNN #Connectivity #StructuralConnectivity #FunctionalConnectivity

#arxivfeed :

"Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings"
https://www.biorxiv.org/content/10.1101/2022.11.17.516914v1

#Neuroscience #Neuro #Brain #NeuralNetwork #RNN #Connectivity #StructuralConnectivity #FunctionalConnectivity

#arxivfeed :

"Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings"
https://www.biorxiv.org/content/10.1101/2022.11.17.516914v1

#Neuroscience #Neuro #Brain #NeuralNetwork #RNN #Connectivity #StructuralConnectivity #FunctionalConnectivity

#arxivfeed :

"Improved high-dimensional multivariate autoregressive model estimation of human electrophysiological data using fMRI priors"
https://www.biorxiv.org/content/10.1101/2022.11.18.516669v1

#Neuroscience #Neuro #Brain #Network #Neuroimaging #Connectivity #MVAR #fMRI #iEEG #EEG

#arxivfeed :

"Asymptotics for The k-means"
https://arxiv.org/abs/2211.10015

#MachineLearning #UnsupervisedLearning #kMeans #Clustering

#arxivfeed :

"High-resolution image reconstruction with latent diffusion models from human brain activity"
https://www.biorxiv.org/content/10.1101/2022.11.18.517004v1

#Neuroscience #Neuro #Brain #Neuroimaging #fMRI #MachineLearning #DiffusionModel #VisualSystem #Vision

#arxivfeed :

"Robust DNN Surrogate Models with Uncertainty Quantification via Adversarial Training"
https://arxiv.org/abs/2211.09954

#MachineLearning #DeepLearning #SurrogateModels #AdversarialTraining #UncertaintyQuantification #Simulation