{"id":361313,"date":"2017-03-15T04:21:34","date_gmt":"2017-03-15T11:21:34","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=361313"},"modified":"2025-08-06T11:57:59","modified_gmt":"2025-08-06T18:57:59","slug":"frontiers-in-ai","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/frontiers-in-ai\/","title":{"rendered":"Frontiers in AI – Max Welling"},"content":{"rendered":"\n\n

21 Station Road
\nCambridge
\nCB1 2FB<\/p>\n

 <\/p>\n

View the whole series on talks.cam (opens in new tab)<\/span><\/a><\/p>\n

View this talk on talks.cam (opens in new tab)<\/span><\/a><\/p>\n

 Opens in a new tab<\/span><\/p>\n

 <\/p>\n

Frontiers in Artificial Intelligence<\/span> is a series of public lectures at Microsoft Research Cambridge featur-ing leading researchers in the field, focusing on the cutting edge topics at the intersection of machine learning, statistics, and artificial intelligence. Students, scientists, and engineers in academia and in-dustry are all welcome to join us for these exciting talks and the opportunity to socialize with the Cam-bridge AI\/ML community.<\/p>\n

 <\/p>\n

Generalizing Convolutions for Deep Learning<\/h3>\n

Prof. Dr. Max Welling, University of Amsterdam<\/h4>\n

Arguably, most excitement about deep learning revolves around the performance of convolutional neural networks and their ability to automatically extract useful features from signals. In this talk I will present work from AMLAB where we generalize these convolutions. First we study convolutions on graphs and propose a simple new method to learn embeddings of graphs which are subsequently used for semi-supervised learning and link prediction. We discuss applications to recommender systems and knowledge graphs. Second we propose a new type of convolution on regular grids based on group transformations. This generalizes normal convolutions based on translations to larger groups including the rotation group. Both methods often result in significant improvements relative to the current state of the art.<\/p>\n

Joint work with Thomas Kipf, Rianne van den Berg and Taco Cohen.<\/p>\n

<\/h3>\n

\u00a0<\/strong>Opens in a new tab<\/span><\/p>\n

Wednesday May 3<\/h3>\n

Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning<\/h3>\n

Prof. Aapo Hyvarinen, Gatsby Computational Neuroscience Unit, University College London<\/h4>\n

Opens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

21 Station Road Cambridge CB1 2FB   View the whole series on talks.cam (opens in new tab) View this talk on talks.cam (opens in new tab)  Opens in a new tab   Frontiers in Artificial Intelligence is a series of public lectures at Microsoft Research Cambridge featur-ing leading researchers in the field, focusing on the […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2017-03-29","msr_enddate":"2017-03-29","msr_location":"Microsoft Research Cambridge UK","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"","msr_event_link_redirect":false,"msr_event_time":"13:00 - 14:30","msr_hide_region":true,"msr_private_event":false,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13556],"msr-region":[239178],"msr-event-type":[197944],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-361313","msr-event","type-msr-event","status-publish","hentry","msr-research-area-artificial-intelligence","msr-region-europe","msr-event-type-hosted-by-microsoft","msr-locale-en_us"],"msr_about":"\n\n

21 Station Road
\nCambridge
\nCB1 2FB<\/p>\n

 <\/p>\n

View the whole series on talks.cam (opens in new tab)<\/span><\/a><\/p>\n

View this talk on talks.cam (opens in new tab)<\/span><\/a><\/p>\n

 Opens in a new tab<\/span><\/p>\n

 <\/p>\n

Frontiers in Artificial Intelligence<\/span> is a series of public lectures at Microsoft Research Cambridge featur-ing leading researchers in the field, focusing on the cutting edge topics at the intersection of machine learning, statistics, and artificial intelligence. Students, scientists, and engineers in academia and in-dustry are all welcome to join us for these exciting talks and the opportunity to socialize with the Cam-bridge AI\/ML community.<\/p>\n

 <\/p>\n

Generalizing Convolutions for Deep Learning<\/h3>\n

Prof. Dr. Max Welling, University of Amsterdam<\/h4>\n

Arguably, most excitement about deep learning revolves around the performance of convolutional neural networks and their ability to automatically extract useful features from signals. In this talk I will present work from AMLAB where we generalize these convolutions. First we study convolutions on graphs and propose a simple new method to learn embeddings of graphs which are subsequently used for semi-supervised learning and link prediction. We discuss applications to recommender systems and knowledge graphs. Second we propose a new type of convolution on regular grids based on group transformations. This generalizes normal convolutions based on translations to larger groups including the rotation group. Both methods often result in significant improvements relative to the current state of the art.<\/p>\n

Joint work with Thomas Kipf, Rianne van den Berg and Taco Cohen.<\/p>\n

<\/h3>\n

\u00a0<\/strong>Opens in a new tab<\/span><\/p>\n

Wednesday May 3<\/h3>\n

Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning<\/h3>\n

Prof. Aapo Hyvarinen, Gatsby Computational Neuroscience Unit, University College London<\/h4>\n

Opens in a new tab<\/span><\/p>\n","tab-content":[{"id":0,"name":"About","content":" \r\n\r\nFrontiers in Artificial Intelligence<\/span> is a series of public lectures at Microsoft Research Cambridge featur-ing leading researchers in the field, focusing on the cutting edge topics at the intersection of machine learning, statistics, and artificial intelligence. Students, scientists, and engineers in academia and in-dustry are all welcome to join us for these exciting talks and the opportunity to socialize with the Cam-bridge AI\/ML community.\r\n\r\n \r\n

Generalizing Convolutions for Deep Learning<\/h3>\r\n

Prof. Dr. Max Welling, University of Amsterdam<\/h4>\r\nArguably, most excitement about deep learning revolves around the performance of convolutional neural networks and their ability to automatically extract useful features from signals. In this talk I will present work from AMLAB where we generalize these convolutions. First we study convolutions on graphs and propose a simple new method to learn embeddings of graphs which are subsequently used for semi-supervised learning and link prediction. We discuss applications to recommender systems and knowledge graphs. Second we propose a new type of convolution on regular grids based on group transformations. This generalizes normal convolutions based on translations to larger groups including the rotation group. Both methods often result in significant improvements relative to the current state of the art.\r\n\r\nJoint work with Thomas Kipf, Rianne van den Berg and Taco Cohen.\r\n

<\/h3>\r\n\u00a0<\/strong>"},{"id":1,"name":"Upcoming talks","content":"

Wednesday May 3<\/h3>\r\n

Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning<\/h3>\r\n

Prof. Aapo Hyvarinen, Gatsby Computational Neuroscience Unit, University College London<\/h4>"}],"msr_startdate":"2017-03-29","msr_enddate":"2017-03-29","msr_event_time":"13:00 - 14:30","msr_location":"Microsoft Research Cambridge UK","msr_event_link":"","msr_event_recording_link":"","msr_startdate_formatted":"March 29, 2017","msr_register_text":"Watch now","msr_cta_link":"","msr_cta_text":"","msr_cta_bi_name":"","featured_image_thumbnail":null,"event_excerpt":"  Frontiers in Artificial Intelligence is a series of public lectures at Microsoft Research Cambridge featur-ing leading researchers in the field, focusing on the cutting edge topics at the intersection of machine learning, statistics, and artificial intelligence. Students, scientists, and engineers in academia and in-dustry are all welcome to join us for these exciting talks and the opportunity to socialize with the Cam-bridge AI\/ML community.   Generalizing Convolutions for Deep Learning Prof. Dr. Max Welling,…","msr_research_lab":[199561],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[],"related-opportunities":[],"related-publications":[],"related-videos":[],"related-posts":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/361313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-event"}],"version-history":[{"count":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/361313\/revisions"}],"predecessor-version":[{"id":1147177,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/361313\/revisions\/1147177"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=361313"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=361313"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=361313"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=361313"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=361313"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=361313"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=361313"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=361313"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=361313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}