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Estimating Undocumented Infections By Data Driven Approach

It's simple to use data to determine how many undocumented infections there are and the adequate reproductive number. A compartmental model includes asymptomatic and presymptomatic contagions, which can be used to figure out how many unreported infections there are and the proper reproductive number.
Suleman Shah
Apr 14, 2022

Estimating Undocumented Infections By Data Driven Approach

Estimating Undocumented Infections By Data Driven Approach

It's simple to use data to determine how many undocumented infections there are and the adequate reproductive number. A compartmental model includes asymptomatic and presymptomatic contagions, which can be used to figure out how many unreported infections there are and the proper reproductive number.
It's simple to use data to determine how many undocumented infections there are and the adequate reproductive number. A compartmental model includes asymptomatic and presymptomatic contagions, which can be used to figure out how many unreported infections there are and the proper reproductive number.
Suleman Shah
Apr 14, 2022

Divergent Representations Of Ethological Visual Inputs Emerge From Supervised, Unsupervised, And Reinforcement Learning

Divergent Representations Of Ethological Visual Inputs Emerge From Supervised, Unsupervised, And Reinforcement Learning

Artificial neural systems trained using supervised, unsupervised, and reinforcement learning all acquire internal representations of high dimensional input. To what extent these representations depend on the different learning objectives is largely unknown.
Artificial neural systems trained using supervised, unsupervised, and reinforcement learning all acquire internal representations of high dimensional input. To what extent these representations depend on the different learning objectives is largely unknown.
Suleman Shah
Mar 13, 2022

Biolcnet: Reward-Modulated Locally Connected Spiking Neural Networks

Biolcnet: Reward-Modulated Locally Connected Spiking Neural Networks

Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the biological visual system. To propose a more biologically plausible solution, we designed a reward modulated locally connected spiking neural network (SNN) trained using spike-timing-dependent plasticity (STDP) and its reward-modulated variant (R-STDP) learning rules.
Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the biological visual system. To propose a more biologically plausible solution, we designed a reward modulated locally connected spiking neural network (SNN) trained using spike-timing-dependent plasticity (STDP) and its reward-modulated variant (R-STDP) learning rules.
Suleman Shah
Mar 13, 2022

Learning To Automate Cryo-Electron Microscopy Data Collection With Ptolemy

Learning To Automate Cryo-Electron Microscopy Data Collection With Ptolemy

Over the past decade, cryogenic electron microscopy (cryo-EM) has emerged as a primary method for determining near-native, near-atomic resolution 3D structures of biological macromolecules. Automated approaches to improve throughput and efficiency while lowering costs are needed to meet the increasing demand for cryo-EM. Currently, in the process of collecting high-magnification cryo-EM micrographs, data collection requires human input and manual tuning of parameters, as expert operators must navigate low- and medium-magnification images to find good high-magnification collection locations.
Over the past decade, cryogenic electron microscopy (cryo-EM) has emerged as a primary method for determining near-native, near-atomic resolution 3D structures of biological macromolecules. Automated approaches to improve throughput and efficiency while lowering costs are needed to meet the increasing demand for cryo-EM. Currently, in the process of collecting high-magnification cryo-EM micrographs, data collection requires human input and manual tuning of parameters, as expert operators must navigate low- and medium-magnification images to find good high-magnification collection locations.
Suleman Shah
Jan 17, 2022

A Formalism For The Long-Distance Magnetic Field Generated By Populations Of Neurons

A Formalism For The Long-Distance Magnetic Field Generated By Populations Of Neurons

Brain activity can be measured using magnetic fields located at some distance from the brain, a technique called magneto-encephalography (MEG). The origin of such magnetic fields are the ionic currents involved in neuronal activity. While these processes are well known at the microscopic scale, it is less clear how large populations of neurons generate magnetic fields.
Brain activity can be measured using magnetic fields located at some distance from the brain, a technique called magneto-encephalography (MEG). The origin of such magnetic fields are the ionic currents involved in neuronal activity. While these processes are well known at the microscopic scale, it is less clear how large populations of neurons generate magnetic fields.
Suleman Shah
Jan 17, 2022

Zelikow: I Didn’t Ask Rice About 2002 Torture Decisions « The Washington Independent

Zelikow: I Didn’t Ask Rice About 2002 Torture Decisions « The Washington Independent

Suleman Shah
Jul 31, 2020
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