Çaǧlar Gülçehre

50.2k citations
26 papers · 1.7k indexed · 1 hit paper · h-index 11

Çaǧlar Gülçehre

23 papers receiving 1.6k citations

Hit Papers

How to Construct Deep Recurrent Neural Networks4002014202620182022100200300400

Peers

Çaǧlar Gülçehre
Comparison fields: 5 of 138
  • Artificial Intelligence 1.0k
  • Computer Vision and Pattern Recognition 526
  • Signal Processing 188
  • Experimental and Cognitive Psychology 169
  • Computational Mathematics 3
Replace Pascal Lamblin with:
Pascal Lamblin Canada
Maurizio Filippone United Kingdom
Hong-Han Shuai Taiwan
Pengjiang Qian China
Yann Dauphin United States
Mikel Luján United Kingdom
Shijie Hao China
Mohammad Rahmati Iran
Shayok Chakraborty United States
Yizhang Jiang China
Çaǧlar Gülçehre relative to Pascal Lamblin Canada Pascal Lamblin's profile →
Citations per field
00.5×1.5×1.8×
Pascal Lamblin · 1×
Citations per year

Countries citing papers authored by Çaǧlar Gülçehre

Since Specialization
Citations

This map shows the geographic impact of Çaǧlar Gülçehre's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Çaǧlar Gülçehre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Çaǧlar Gülçehre more than expected).

Fields of papers citing papers by Çaǧlar Gülçehre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Çaǧlar Gülçehre. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Çaǧlar Gülçehre. The network helps show where Çaǧlar Gülçehre may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Çaǧlar Gülçehre, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Çaǧlar Gülçehre Line = papers co-authored together Çaǧlar Gülçehre links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20240
4
Improving the Gating Mechanism of Recurrent Neural Networks
20205
5
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning.
20202
6
Critic Regularized Regression
20201
7
Stabilizing Transformers for Reinforcement Learning
20209
8 20202
9 201951
10
Sample-efficient adaptive text-to-speech
201816
11
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL
20189
12
Memory Augmented Neural Networks for Natural Language Processing
20171
13
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
20176
14 20172
15 2015261
16 2015263
17 201524
18
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
2014231
19
How to Construct Deep Recurrent Neural Networksbreakdown →
2014400
20
Learned-norm pooling for deep neural networks.
20137

About Çaǧlar Gülçehre

Çaǧlar Gülçehre is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Science Applications and Safety Research, having authored 26 papers that have together received 1.7k indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Reinforcement Learning in Robotics (7 papers), Natural Language Processing Techniques (7 papers), Neural Networks and Applications (5 papers), Multimodal Machine Learning Applications (5 papers), Neural Networks and Reservoir Computing (2 papers), Ferroelectric and Negative Capacitance Devices (2 papers) and Music and Audio Processing (2 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computer Vision and Pattern Recognition (526 citations), Signal Processing (188 citations), Experimental and Cognitive Psychology (169 citations) and Computational Mathematics (3 citations). Çaǧlar Gülçehre has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Yoshua Bengio, Razvan Pascanu, Kyunghyun Cho, Kyunghyun Cho, Jun‐Young Chung, Yann Dauphin, Ramesh Nallapati, Bowen Zhou, Sungjin Ahn and Surya Ganguli. Their work appears in journals such as Neural Computation, Computer Speech & Language, Journal on Multimodal User Interfaces, Empirical Methods in Natural Language Processing and arXiv (Cornell University).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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