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Author Information
Ayse Cakmak (Georgia Institute of Technology)
Yunkai Zhang (UC Santa Barbara)
Srijith Prabhakarannair Kusumam (Indian Institute of Technology Hyderabad)
Mohamed Osama Ahmed (Borealis AI)
Xintao Wu (University of Arkansas)
Dr. Xintao Wu is the professor and the Charles D. Morgan/Acxiom Endowed Graduate Research Chair in Database and leads Social Awareness and Intelligent Learning (SAIL) Lab in Computer Science and Computer Engineering Department at University of Arkansas.
Jayesh Choudhari (Indian Institute of Technology Gandhinagar)
David I Inouye (Purdue University)
Thomas Taylor (University of Oxford)
Michel Besserve (MPI for Intelligent Systems)
Ali Caner Turkmen (Bogazici University)
Kazi Islam (University of California, Riverside)
Antonio Artés (Universidad Carlos III de Madrid)
Amrith Setlur (Carnegie Mellon University)
Zhanghua Fu (The Chinese University of Hong Kong, Shenzhen)
Zhen Han (Siemens AG)
I am an AI researcher at Siemens Corporate Technology. I have completed my Ph.D. study with a specialization in Machine Learning at the University of Munich. My supervisor is Prof. Volker Tresp. My research interests include Machine Learning on Knowledge Graphs and Natural Language Processing. I have published eight 1st/(co-first) author papers and 10+ co-author papers at top conferences, e.g., ICLR and EMNLP. In 2021, I have been selected as 1 of 51 national winners to receive a research grant (100,000 Euros) from the German Federal Ministry of Education and Research. With this funding, I'm leading a small research team focusing on knowledge-enhanced language modeling and reasoning. Besides, I received the Best Paper Runner-Up Award at the international knowledge graph conference AKBC in 2020. In 2019, I finished my master’s degree at the Technical University of Munich focusing on robotics, cognition, and intelligence. Prior to my master's study, I graduated from the Karlsruhe Institute of Technology (a member of the German elite universities) with distinction.
Abir De (Max Planck Insitute for Software Systems)
Nan Du (Google Brain)
Pablo Sanchez-Martin (Max Planck Institute for Intelligence Systems)
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2021 : [O2] Not too close and not too far: enforcing monotonicity requires penalizing the right points »
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2019 : Poster Session »
Ethan Harris · Tom White · Oh Hyeon Choung · Takashi Shinozaki · Dipan Pal · Katherine L. Hermann · Judy Borowski · Camilo Fosco · Chaz Firestone · Vijay Veerabadran · Benjamin Lahner · Chaitanya Ryali · Fenil Doshi · Pulkit Singh · Sharon Zhou · Michel Besserve · Michael Chang · Anelise Newman · Mahesan Niranjan · Jonathon Hare · Daniela Mihai · Marios Savvides · Simon Kornblith · Christina M Funke · Aude Oliva · Virginia de Sa · Dmitry Krotov · Colin Conwell · George Alvarez · Alex Kolchinski · Shengjia Zhao · Mitchell Gordon · Michael Bernstein · Stefano Ermon · Arash Mehrjou · Bernhard Schölkopf · John Co-Reyes · Michael Janner · Jiajun Wu · Josh Tenenbaum · Sergey Levine · Yalda Mohsenzadeh · Zhenglong Zhou -
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2018 Poster: Deep Reinforcement Learning of Marked Temporal Point Processes »
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2016 Poster: Learning and Forecasting Opinion Dynamics in Social Networks »
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2015 Poster: Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial »
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2014 Poster: Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs »
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2013 Poster: Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. »
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