Which institute has a higher number of publication citations, the institution of the writer of 'Partitioning a Graph in O(|A| log2 |V|)' or the author affiliated with STMicroelectronics (France)?
French National Centre for Scientific Research
Sepp Hochreiter: The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions. (1998) authored by Sepp Hochreiter. Markus Hofmarcher et al.: Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. (2019) authored by Sepp Hochreiter. Sepp Hochreiter is the author of Daniel Klotz et al.: Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. (2022) and Aleksandra Gruca et al.: Entangled Residual Mappings. (2021) authored by Sepp Hochreiter. Vihang Patil et al.: Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. (2022 Sepp Hochreiter is the author of RUDDER: Return Decomposition for Delayed Rewards, which overcomes the problem of numerical instability in training recurrent models. Sepp Hochreiter is also the author of Vihang Prakash Patil and Pedro Herruzo et al.: High-resolution multi-channel weather forecasting - First insights on transfer learning from the Weather4cast Competitions 2021. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hoch
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Question: Which institute has a higher number of publication citations, the institution of the writer of 'Partitioning a Graph in O(|A| log2 |V|)' or the author affiliated with STMicroelectronics (France)?
Context: Sepp Hochreiter: The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions. (1998) authored by Sepp Hochreiter. Markus Hofmarcher et al.: Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. (2019) authored by Sepp Hochreiter. Sepp Hochreiter is the author of Daniel Klotz et al.: Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. (2022) and Aleksandra Gruca et al.: Entangled Residual Mappings. (2021) authored by Sepp Hochreiter. Vihang Patil et al.: Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. (2022 Sepp Hochreiter is the author of RUDDER: Return Decomposition for Delayed Rewards, which overcomes the problem of numerical instability in training recurrent models. Sepp Hochreiter is also the author of Vihang Prakash Patil and Pedro Herruzo et al.: High-resolution multi-channel weather forecasting - First insights on transfer learning from the Weather4cast Competitions 2021. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hochreiter introduced modern Hopfield networks with continuous states and applied them to the task of immune repertoire classification. '<unk>. Hoch
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