TP1 Leveraging Complex Prior Knowledge for Learning
author:
Neil Lawrence,
School of Mathematics, University of Manchester
You might be experiencing some problems with Your Video player.
| Slides | |
| 0:00 | TP1: Leveraging Complex Prior Knowledge in Learning |
| 1:21 | Outline 1 |
| 1:25 | PASCAL II Thematic Programmes - 1 |
| 1:36 | PASCAL II Thematic Programmes - 2 |
| 1:42 | PASCAL II Thematic Programmes - 3 |
| 2:08 | PASCAL II Thematic Programmes - 4 |
| 2:17 | PASCAL II Thematic Programmes - 5 |
| 2:25 | PASCAL II Thematic Programmes - 6 |
| 2:38 | PASCAL II Thematic Programmes - 7 |
| 3:15 | PASCAL II Thematic Programmes - 8 |
| 3:45 | Machine Learning History - 1 |
| 4:29 | Machine Learning History - 2 |
| 5:52 | Machine Learning History - 3 |
| 6:24 | Machine Learning History - 4 |
| 6:28 | Machine Learning History - 5 |
| 6:30 | Machine Learning History - 6 |
| 6:46 | Machine Learning History - 7 |
| 6:53 | The Future - 1 |
| 7:11 | The Future - 2 |
| 7:21 | The Future - 3 |
| 7:41 | The Future - 4 |
| 8:03 | The Future - 5 |
| 8:17 | The Future - 6 |
| 8:18 | The Future - 7 |
| 8:31 | What Can we do Today? - 1 |
| 9:59 | What Can we do Today? - 2 |
| 10:14 | What Can we do Today? - 3 |
| 10:18 | What Can we do Today? - 4 |
| 10:22 | What Can we do Today? - 5 |
| 10:35 | What Can we do Today? - 6 |
| 11:17 | What Can we do Today? - 7 |
| 11:22 | What Can we do Today? - 8 |
| 11:32 | Outline 2 |
| 11:35 | The Methodologies - 1 |
| 11:49 | The Methodologies - 2 |
| 11:53 | The Methodologies - 3 |
| 12:02 | The Methodologies - 4 |
| 12:31 | The Methodologies - 5 |
| 12:35 | The Methodologies - 6 |
| 13:02 | The Methodologies - 7 |
| 13:34 | The Methodologies - 8 |
| 13:39 | The Methodologies - 9 |
| 14:10 | The Methodologies - 10 |
| 14:18 | The Methodologies - 11 |
| 15:09 | The Methodologies - 12 |
| 15:11 | Outline 3 |
| 15:15 | Common Themes - 1 |
| 15:31 | Common Themes - 2 |
| 15:49 | Common Themes - 3 |
| 15:53 | Common Themes - 4 |
| 15:56 | Common Themes - 5 |
| 16:00 | Common Themes - 6 |
| 16:02 | Common Themes - 7 |
| 16:24 | Computational and Systems Biology - 1 |
| 16:43 | Computational and Systems Biology - 2 |
| 17:04 | Computational and Systems Biology - 3 |
| 17:22 | Computational and Systems Biology - 4 |
| 17:28 | Computational and Systems Biology - 5 |
| 18:07 | Computational and Systems Biology - 6 |
| 18:10 | Computational and Systems Biology - 7 |
| 18:14 | Computational and Systems Biology - 8 |
| 18:26 | What's Out There? - 1 |
| 18:30 | What's Out There? - 2 |
| 18:55 | What's Out There? - 3 |
| 19:51 | What's Out There? - 4 |
| 19:57 | What's Out There? - 5 |
| 20:07 | What's Out There? - 6 |
| 20:27 | Case Study - 1 |
| 20:59 | Case Study - 2 |
| 21:47 | Case Study - 3 |
| 21:56 | Case Study - 4 |
| 22:25 | Differential Equations |
| 22:52 | Bayes Factors |
| 23:33 | Hypothesis Implications |
| 23:44 | Results from siRNA Knock Down Experiments |
| 23:52 | Hypothesis Implications |
| 23:57 | Results from siRNA Knock Down Experiments |
| 24:08 | Hypothesis Implications |
| 24:14 | Results from siRNA Knock Down Experiments |
| 24:27 | Computational Bio Conclusions - 1 |
| 24:30 | Computational Bio Conclusions - 2 |
| 24:50 | Computational Bio Conclusions - 3 |
| 24:54 | Computational Bio Conclusions - 4 |
| 24:56 | Computational Bio Conclusions - 5 |
| 24:58 | Computational Bio Conclusions - 6 |
| 25:07 | Text and Language Processing - 1 |
| 25:32 | Text and Language Processing - 2 |
| 25:36 | Text and Language Processing - 3 |
| 25:46 | Text and Language Processing - 4 |
| 25:52 | Text and Language Processing - 5 |
| 26:19 | Text and Language Processing - 6 |
| 26:41 | Text and Language Processing - 7 |
| 26:46 | Historic Perspective (Language) - 1 |
| 26:48 | Historic Perspective (Language) - 2 |
| 26:51 | Historic Perspective (Language) - 3 |
| 26:58 | Historic Perspective (Language) - 4 |
| 27:02 | Historic Perspective (Language) - 5 |
| 27:04 | Historic Perspective (Language) - 6 |
| 27:07 | Historic Perspective (Language) - 7 |
| 27:19 | Historic Perspective (Language) - 8 |
| 27:29 | Implicit Prior Knowledge in Data Driven Systems - 1 |
| 27:31 | Implicit Prior Knowledge in Data Driven Systems - 2 |
| 27:41 | Implicit Prior Knowledge in Data Driven Systems - 3 |
| 27:44 | Implicit Prior Knowledge in Data Driven Systems - 4 |
| 27:59 | Implicit Prior Knowledge in Data Driven Systems - 5 |
| 28:21 | Towards Explicit Prior Knowledge - 1 |
| 28:29 | Towards Explicit Prior Knowledge - 2 |
| 28:39 | Towards Explicit Prior Knowledge - 3 |
| 28:42 | Towards Explicit Prior Knowledge - 4 |
| 28:46 | Towards Explicit Prior Knowledge - 5 |
| 28:55 | Towards Explicit Prior Knowledge - 6 |
| 28:59 | Towards Explicit Prior Knowledge - 7 |
| 29:04 | Towards Explicit Prior Knowledge - 8 |
| 29:16 | Towards Explicit Prior Knowledge - 9 |
| 29:22 | Towards Explicit Prior Knowledge - 10 |
| 29:34 | Surge of Publications |
| 29:45 | The Challenge of Incorporating Expert Knowledge - 1 |
| 30:10 | The Challenge of Incorporating Expert Knowledge - 2 |
| 30:18 | The Challenge of Incorporating Expert Knowledge - 3 |
| 30:22 | The Challenge of Incorporating Expert Knowledge - 4 |
| 30:41 | The Challenge of Incorporating Expert Knowledge - 5 |
| 31:05 | Outline 4 |
| 31:39 | Computational and Systems Biology |
| 32:49 | Stochastic Processes and Dierential Equations |
| 34:29 | Bayesian Workshop |
| 35:41 | Language Workshop |
| 36:05 | Other Workshops |
Lecture rating
| People found this lecture: | ||
| Worth seeing | ||
| because it is: | ||
| Valuable and informative | ||
| Well presented | ||
| Easily understandable | ||
| Acceptably recorded | ||
| You need to login to cast your vote. | ||
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Related content
Visitors who watched this lecture also watched...
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !





