Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Markovich, Thomas"'
Modern large language models (LLMs) represent a paradigm shift in what can plausibly be expected of machine learning models. The fact that LLMs can effectively generate sensible answers to a diverse range of queries suggests that they would be useful
Externí odkaz:
http://arxiv.org/abs/2405.15765
Autor:
Markovich, Thomas
Graph convolutional neural networks (GCNs) operate by aggregating messages over local neighborhoods given the prediction task under interest. Many GCNs can be understood as a form of generalized diffusion of input features on the graph, and significa
Externí odkaz:
http://arxiv.org/abs/2307.11234
Autor:
Cai, Vanessa, Prabakar, Pradeep, Rebuelta, Manuel Serrano, Rosen, Lucas, Monti, Federico, Janocha, Katarzyna, Lazovich, Tomo, Raj, Jeetu, Shrinivasan, Yedendra, Li, Hao, Markovich, Thomas
Recommendation systems are a core feature of social media companies with their uses including recommending organic and promoted contents. Many modern recommendation systems are split into multiple stages - candidate generation and heavy ranking - to
Externí odkaz:
http://arxiv.org/abs/2302.13915
Graph attention networks estimate the relational importance of node neighbors to aggregate relevant information over local neighborhoods for a prediction task. However, the inferred attentions are vulnerable to spurious correlations and connectivity
Externí odkaz:
http://arxiv.org/abs/2210.10946
Autor:
Chamberlain, Benjamin Paul, Shirobokov, Sergey, Rossi, Emanuele, Frasca, Fabrizio, Markovich, Thomas, Hammerla, Nils, Bronstein, Michael M., Hansmire, Max
Publikováno v:
The Eleventh International Conference on Learning Representations 2023 (oral - top 5%)
Many Graph Neural Networks (GNNs) perform poorly compared to simple heuristics on Link Prediction (LP) tasks. This is due to limitations in expressive power such as the inability to count triangles (the backbone of most LP heuristics) and because the
Externí odkaz:
http://arxiv.org/abs/2209.15486
Autor:
Di Giovanni, Francesco, Rowbottom, James, Chamberlain, Benjamin P., Markovich, Thomas, Bronstein, Michael M.
Graph Neural Networks (GNNs) typically operate by message-passing, where the state of a node is updated based on the information received from its neighbours. Most message-passing models act as graph convolutions, where features are mixed by a shared
Externí odkaz:
http://arxiv.org/abs/2206.10991
Autor:
El-Kishky, Ahmed, Markovich, Thomas, Leung, Kenny, Portman, Frank, Haghighi, Aria, Xiao, Ying
Candidate retrieval is the first stage in recommendation systems, where a light-weight system is used to retrieve potentially relevant items for an input user. These candidate items are then ranked and pruned in later stages of recommender systems us
Externí odkaz:
http://arxiv.org/abs/2205.06205
Autor:
El-Kishky, Ahmed, Markovich, Thomas, Park, Serim, Verma, Chetan, Kim, Baekjin, Eskander, Ramy, Malkov, Yury, Portman, Frank, Samaniego, Sofía, Xiao, Ying, Haghighi, Aria
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022)
Social networks, such as Twitter, form a heterogeneous information network (HIN) where nodes represent domain entities (e.g., user, content, advertiser, etc.) and edges represent one of many entity interactions (e.g, a user re-sharing content or "fol
Externí odkaz:
http://arxiv.org/abs/2202.05387
Autor:
Markovich, Thomas, Blood-Forsythe, Martin A., Rappoport, Dmitrij, Kim, Dasol, Aspuru-Guzik, Alán
Recent work has shown that a fully many-body treatment of noncovalent interactions, such as that given by the method of many-body dispersion (MBD), is vital to accurately modeling the structure and energetics of many molecular systems with density fu
Externí odkaz:
http://arxiv.org/abs/1605.04987
Autor:
Blood-Forsythe, Martin A., Markovich, Thomas, DiStasio Jr., Robert A., Car, Roberto, Aspuru-Guzik, Alán
Publikováno v:
Chem. Sci., 7, (2016) 1712-1728
Accurate treatment of the long-range electron correlation energy, including van der Waals (vdW) or dispersion interactions, is essential for describing the structure, dynamics, and function of a wide variety of systems. Among the most accurate models
Externí odkaz:
http://arxiv.org/abs/1509.00480