[Coursera] Computational Neuroscience

磁力链接/BT种子名称

[Coursera] Computational Neuroscience

磁力链接/BT种子简介

种子哈希：09415640a0c9125d10fe6a67aa9c88a84286aefa
文件大小：780.14M
已经下载：2035次
下载速度：极快
收录时间：2017-02-09
最近下载：2024-11-05

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:09415640A0C9125D10FE6A67AA9C88A84286AEFA
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 暗网禁地 91短视频 TikTok成人版 PornHub 草榴社区 乱伦社区

最近搜索

文件列表

  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8 - 1 - 1 Neurons as Classifiers and Supervised Learning (2557).mp4 34.3 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6 - 3 - 3 The Fascinating World of Recurrent Networks (2535).mp4 33.6 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6 - 1 - 1 Modeling Connections between Neurons (2428).mp4 32.6 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1 - 4 - 4 The Electrical Personality of Neurons (2302).mp4 32.4 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/05 - Guest Lecture Eric Shea-Brown (22-52)/5 - 5 - Guest Lecture Eric Shea-Brown (2252).mp4 31.8 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/01 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (24-17)/7 - 1 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (2417).mp4 31.8 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/03 - 3 Sparse Coding and Predictive Coding (23-54)/7 - 3 - 3 Sparse Coding and Predictive Coding (2354).mp4 31.6 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8 - 3 - 3 Reinforcement Learning Time for Action (1949).mp4 30.7 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/02 - 2 Population Coding and Bayesian Estimation (24-44)/3 - 2 - 2 Population Coding and Bayesian Estimation (2444).mp4 29.6 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6 - 2 - 2 Introduction to Network Models (2147).mp4 28.7 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/04 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (20-06)/8 - 4 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (2006).mp4 28.6 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7 - 2 - 2 Introduction to Unsupervised Learning (2206).mp4 28.5 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).mp4 24.7 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/5 - 4 - 4 A Forest of Dendrites (1919).mp4 24.2 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).mp4 23.9 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1 - 6 - 6 Time to Network Brain Areas and their Function (1706).mp4 23.4 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/01 - 1 Neural Decoding and Signal Detection Theory (18-55)/3 - 1 - 1 Neural Decoding and Signal Detection Theory (1855).mp4 22.7 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/4 - 2 - 2 Calculating Information in Spike Trains (1725).mp4 22.1 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).mp4 21.2 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).mp4 19.2 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/04 - Guest Lecture Fred Rieke (14-01)/3 - 4 - Guest Lecture Fred Rieke (1401).mp4 18.3 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/2 - 4 - 4 Neural Encoding Variability (2352).mp4 18.1 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8 - 2 - 2 Reinforcement Learning Predicting Rewards (1301).mp4 17.2 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/03 - 3 Neural Encoding Feature Selection (22-13)/2 - 3 - 3 Neural Encoding Feature Selection (2213).mp4 16.7 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1 - 3 - 3 Computational Neuroscience Mechanistic and Interpretive Models (1235).mp4 16.7 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).mp4 16.6 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).mp4 16.6 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/3 - 3 - 3 Reading Minds Stimulus Reconstruction (1159).mp4 15.8 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/01 - 1 What is the Neural Code (19-18)/2 - 1 - 1 What is the Neural Code (1918).mp4 15.8 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).mp4 15.7 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/Lecture 4 part 1.pdf 8.9 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/Lecture 5 Part 1.pdf 8.7 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/02 - 2 Neural Encoding Simple Models (12-06)/2 - 2 - 2 Neural Encoding Simple Models (1206).mp4 8.6 MB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1 - 1 - 1 Course Introduction and Logistics (0605).mp4 8.5 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/Lecture 4 part 3.pdf 7.5 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/Lecture 5 Part 3.pdf 4.3 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/Lecture 3 part 3.pdf 4.0 MB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/Lecture 5 Part 2.pdf 3.9 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/02 - 2 Population Coding and Bayesian Estimation (24-44)/Lecture 3 part 2.pdf 3.8 MB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/Lecture 4 part 2.pdf 3.5 MB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/01 - 1 Neural Decoding and Signal Detection Theory (18-55)/Lecture 3 part 1.pdf 3.5 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6.3slides.pdf 2.8 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6.2slides_new.pdf 2.5 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/02 - 2 Neural Encoding Simple Models (12-06)/Lecture 2 part 2.pdf 2.3 MB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6.1slides.pdf 2.2 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/Lecture 2 part 4.pdf 2.2 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/01 - 1 What is the Neural Code (19-18)/Lecture 2 part 1.pdf 2.2 MB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/03 - 3 Neural Encoding Feature Selection (22-13)/Lecture 2 part 3.pdf 1.9 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/03 - 3 Sparse Coding and Predictive Coding (23-54)/7.3.pdf 1.8 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8.1.pdf 1.7 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7.2.pdf 1.5 MB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/01 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (24-17)/7.1.pdf 1.5 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8.3.pdf 1.1 MB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8.2.pdf 885.8 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1.4.pdf 720.9 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1.5-2014.pdf 720.6 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1.2.pdf 619.5 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1.6.pdf 575.8 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1.3.pdf 453.1 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1.1.pdf 346.2 kB
  • lectures.html 82.8 kB
  • index.html 43.3 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/2 - 4 - 4 Neural Encoding Variability (2352).srt 37.1 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8 - 1 - 1 Neurons as Classifiers and Supervised Learning (2557).srt 33.9 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6 - 3 - 3 The Fascinating World of Recurrent Networks (2535).srt 33.8 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/03 - 3 Neural Encoding Feature Selection (22-13)/2 - 3 - 3 Neural Encoding Feature Selection (2213).srt 33.5 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/05 - Guest Lecture Eric Shea-Brown (22-52)/5 - 5 - Guest Lecture Eric Shea-Brown (2252).srt 33.4 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/02 - 2 Population Coding and Bayesian Estimation (24-44)/3 - 2 - 2 Population Coding and Bayesian Estimation (2444).srt 33.3 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/01 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (24-17)/7 - 1 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (2417).srt 32.9 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6 - 1 - 1 Modeling Connections between Neurons (2428).srt 32.6 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/03 - 3 Sparse Coding and Predictive Coding (23-54)/7 - 3 - 3 Sparse Coding and Predictive Coding (2354).srt 32.4 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1 - 4 - 4 The Electrical Personality of Neurons (2302).srt 30.9 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/01 - 1 What is the Neural Code (19-18)/2 - 1 - 1 What is the Neural Code (1918).srt 30.9 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7 - 2 - 2 Introduction to Unsupervised Learning (2206).srt 30.2 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).srt 29.3 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/5 - 4 - 4 A Forest of Dendrites (1919).srt 29.0 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6 - 2 - 2 Introduction to Network Models (2147).srt 28.7 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).srt 28.2 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/01 - 1 Neural Decoding and Signal Detection Theory (18-55)/3 - 1 - 1 Neural Decoding and Signal Detection Theory (1855).srt 27.9 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).srt 27.6 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).srt 25.9 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/4 - 2 - 2 Calculating Information in Spike Trains (1725).srt 25.1 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8 - 3 - 3 Reinforcement Learning Time for Action (1949).srt 24.9 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/04 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (20-06)/8 - 4 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (2006).srt 23.4 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/04 - 4 Neural Encoding Variability (23-52)/2 - 4 - 4 Neural Encoding Variability (2352).txt 22.7 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/01 - 1 Neurons as Classifiers and Supervised Learning (25-57)/8 - 1 - 1 Neurons as Classifiers and Supervised Learning (2557).txt 22.7 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/03 - 3 The Fascinating World of Recurrent Networks (25-35)/6 - 3 - 3 The Fascinating World of Recurrent Networks (2535).txt 22.5 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/02 - 2 Population Coding and Bayesian Estimation (24-44)/3 - 2 - 2 Population Coding and Bayesian Estimation (2444).txt 22.2 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/05 - Guest Lecture Eric Shea-Brown (22-52)/5 - 5 - Guest Lecture Eric Shea-Brown (2252).txt 22.0 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1 - 6 - 6 Time to Network Brain Areas and their Function (1706).srt 21.9 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/01 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (24-17)/7 - 1 - 1 Synaptic Plasticity, Hebbs Rule, and Statistical Learning (2417).txt 21.9 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/01 - 1 Modeling Connections between Neurons (24-28)/6 - 1 - 1 Modeling Connections between Neurons (2428).txt 21.7 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/03 - 3 Sparse Coding and Predictive Coding (23-54)/7 - 3 - 3 Sparse Coding and Predictive Coding (2354).txt 21.7 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/04 - Guest Lecture Fred Rieke (14-01)/3 - 4 - Guest Lecture Fred Rieke (1401).srt 21.3 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/04 - 4 The Electrical Personality of Neurons (23-02)/1 - 4 - 4 The Electrical Personality of Neurons (2302).txt 20.4 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/03 - 3 Neural Encoding Feature Selection (22-13)/2 - 3 - 3 Neural Encoding Feature Selection (2213).txt 20.2 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).srt 20.2 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).srt 20.2 kB
  • 07 - Week 7 Networks that Learn Plasticity in the Brain Learning (Rajesh Rao)/02 - 2 Introduction to Unsupervised Learning (22-06)/7 - 2 - 2 Introduction to Unsupervised Learning (2206).txt 20.2 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/04 - 4 A Forest of Dendrites (19-19)/5 - 4 - 4 A Forest of Dendrites (1919).txt 19.4 kB
  • 06 - Week 6 Computing with Networks (Rajesh Rao)/02 - 2 Introduction to Network Models (21-47)/6 - 2 - 2 Introduction to Network Models (2147).txt 19.3 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/01 - 1 What is the Neural Code (19-18)/2 - 1 - 1 What is the Neural Code (1918).txt 19.1 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/03 - 3 Coding Principles (19-09)/4 - 3 - 3 Coding Principles (1909).txt 18.7 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/01 - 1 Neural Decoding and Signal Detection Theory (18-55)/3 - 1 - 1 Neural Decoding and Signal Detection Theory (1855).txt 18.5 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/03 - 3 Simplified Model Neurons (18-40)/5 - 3 - 3 Simplified Model Neurons (1840).txt 18.3 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/02 - 2 Neural Encoding Simple Models (12-06)/2 - 2 - 2 Neural Encoding Simple Models (1206).srt 17.8 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/05 - 5 Making Connections Synapses (21-59)/1 - 5 - 5 Making Connections Synapses (2159).txt 17.7 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8 - 2 - 2 Reinforcement Learning Predicting Rewards (1301).srt 17.1 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/01 - 1 Information and Entropy (19-12)/4 - 1 - 1 Information and Entropy (1912).txt 17.1 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1 - 3 - 3 Computational Neuroscience Mechanistic and Interpretive Models (1235).srt 17.0 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/3 - 3 - 3 Reading Minds Stimulus Reconstruction (1159).srt 16.9 kB
  • 04 - Week 4 Information Theory Neural Coding (Adrienne Fairhall)/02 - 2 Calculating Information in Spike Trains (17-25)/4 - 2 - 2 Calculating Information in Spike Trains (1725).txt 16.8 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/03 - 3 Reinforcement Learning Time for Action (19-49)/8 - 3 - 3 Reinforcement Learning Time for Action (1949).txt 16.7 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).srt 15.6 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/04 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (20-06)/8 - 4 - Guest Lecture Eb Fetz on Bidirectional Brain-Computer Interfaces (2006).txt 15.6 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/06 - 6 Time to Network Brain Areas and their Function (17-06)/1 - 6 - 6 Time to Network Brain Areas and their Function (1706).txt 14.5 kB
  • compneuro-002-about.json 14.2 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/04 - Guest Lecture Fred Rieke (14-01)/3 - 4 - Guest Lecture Fred Rieke (1401).txt 14.2 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/02 - 2 Spikes (14-09)/5 - 2 - 2 Spikes (1409).txt 13.5 kB
  • 05 - Week 5 Computing in Carbon (Adrienne Fairhall)/01 - 1 Modeling Neurons (13-52)/5 - 1 - 1 Modeling Neurons (1352).txt 13.4 kB
  • 08 - Week 8 Learning from Supervision and Rewards (Rajesh Rao)/02 - 2 Reinforcement Learning Predicting Rewards (13-01)/8 - 2 - 2 Reinforcement Learning Predicting Rewards (1301).txt 11.4 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/03 - 3 Computational Neuroscience Mechanistic and Interpretive Models (12-35)/1 - 3 - 3 Computational Neuroscience Mechanistic and Interpretive Models (1235).txt 11.3 kB
  • 03 - Week 3 Extracting Information from Neurons Neural Decoding (Adrienne Fairhall)/03 - 3 Reading Minds Stimulus Reconstruction (11-59)/3 - 3 - 3 Reading Minds Stimulus Reconstruction (1159).txt 11.3 kB
  • 02 - Week 2 What do Neurons Encode Neural Encoding Models (Adrienne Fairhall)/02 - 2 Neural Encoding Simple Models (12-06)/2 - 2 - 2 Neural Encoding Simple Models (1206).txt 10.8 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/02 - 2 Computational Neuroscience Descriptive Models (11-50)/1 - 2 - 2 Computational Neuroscience Descriptive Models (1150).txt 10.4 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1 - 1 - 1 Course Introduction and Logistics (0605).srt 9.1 kB
  • 01 - Week 1 Introduction Basic Neurobiology (Rajesh Rao)/01 - 1 Course Introduction and Logistics (06-05)/1 - 1 - 1 Course Introduction and Logistics (0605).txt 6.1 kB
  • _README.txt 2.4 kB

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>