Jonathan Binas

2.1k total citations · 1 hit paper
14 papers, 983 citations indexed

About

Jonathan Binas is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Jonathan Binas has authored 14 papers receiving a total of 983 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 9 papers in Electrical and Electronic Engineering and 8 papers in Artificial Intelligence. Recurrent topics in Jonathan Binas's work include Neural dynamics and brain function (8 papers), Advanced Memory and Neural Computing (8 papers) and Neural Networks and Reservoir Computing (3 papers). Jonathan Binas is often cited by papers focused on Neural dynamics and brain function (8 papers), Advanced Memory and Neural Computing (8 papers) and Neural Networks and Reservoir Computing (3 papers). Jonathan Binas collaborates with scholars based in Switzerland, Canada and United States. Jonathan Binas's co-authors include Daniel Neil, Shih‐Chii Liu, Michael Pfeiffer, Peter U. Diehl, Matthew Cook, Giacomo Indiveri, Ueli Rutishauser, Tobi Delbrück, Emre Neftci and Elisabetta Chicca and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nano Letters and Frontiers in Computational Neuroscience.

In The Last Decade

Jonathan Binas

14 papers receiving 951 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing

2015 639 citations Peter U. Diehl, Daniel Neil et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jonathan Binas Switzerland	8	813	523	273	206	89	14	983
J. Parker Mitchell United States	13	801 1.0×	256 0.5×	408 1.5×	189 0.9×	41 0.5×	31	981
Andreas Wild United States	12	872 1.1×	218 0.4×	245 0.9×	133 0.6×	64 0.7×	30	1.0k
Kyungmin Kim South Korea	14	670 0.8×	118 0.2×	97 0.4×	276 1.3×	79 0.9×	48	897
Shruti Kulkarni United States	11	755 0.9×	242 0.5×	376 1.4×	206 1.0×	46 0.5×	41	954
Maryam Parsa United States	11	761 0.9×	206 0.4×	365 1.3×	186 0.9×	91 1.0×	42	971
Chetan Singh Thakur India	16	592 0.7×	165 0.3×	166 0.6×	124 0.6×	192 2.2×	76	855
Zhiwei Li China	13	575 0.7×	105 0.2×	147 0.5×	191 0.9×	56 0.6×	85	841
Morteza Hosseini United States	10	446 0.5×	170 0.3×	223 0.8×	144 0.7×	50 0.6×	19	607
Massimo Giordano United States	8	911 1.1×	125 0.2×	237 0.9×	251 1.2×	116 1.3×	11	959

Countries citing papers authored by Jonathan Binas

Since Specialization

Citations

This map shows the geographic impact of Jonathan Binas'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 Jonathan Binas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Binas more than expected).

Fields of papers citing papers by Jonathan Binas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Binas. 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 Jonathan Binas. The network helps show where Jonathan Binas may publish in the future.

Co-authorship network of co-authors of Jonathan Binas

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Binas. A scholar is included among the top collaborators of Jonathan Binas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jonathan Binas. Jonathan Binas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Krueger, David, Ethan Caballero, Joern-Henrik Jacobsen, et al.. (2021). Out-of-Distribution Generalization via Risk Extrapolation (REx). 5815–5826. 2 indexed citations

Goyal, Anirudh, Shagun Sodhani, Jonathan Binas, et al.. (2020). Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. International Conference on Learning Representations. 2 indexed citations

Hu, Yuhuang, Jonathan Binas, Daniel Neil, Shih‐Chii Liu, & Tobi Delbrück. (2020). DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction. 1–6. 47 indexed citations

Lamb, Alex, Jonathan Binas, Anirudh Goyal, et al.. (2019). State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. International Conference on Machine Learning. 3622–3631. 1 indexed citations

Trabelsi, Chiheb, Olexa Bilaniuk, Ousmane Dia, et al.. (2019). Retrieving Signals with Deep Complex Extractors. 1 indexed citations

Scellier, Benjamin, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, & Yoshua Bengio. (2018). Extending the Framework of Equilibrium Propagation to General Dynamics. International Conference on Learning Representations. 1 indexed citations

Ke, Nan Rosemary, Anirudh Goyal, Olexa Bilaniuk, et al.. (2018). Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. PolyPublie (École Polytechnique de Montréal). 31. 7640–7651. 11 indexed citations

Binas, Jonathan, Daniel Neil, Shih‐Chii Liu, & Tobi Delbrück. (2017). DDD17: End-To-End DAVIS Driving Dataset. Zurich Open Repository and Archive (University of Zurich). 0–0. 33 indexed citations

Binas, Jonathan, Giacomo Indiveri, & Michael Pfeiffer. (2016). Spiking analog VLSI neuron assemblies as constraint satisfaction problem solvers. 2094–2097. 13 indexed citations

10.

Diehl, Peter U., Daniel Neil, Jonathan Binas, et al.. (2015). Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. 1–8. 639 indexed citations breakdown →

11.

Binas, Jonathan, Giacomo Indiveri, & Michael Pfeiffer. (2015). Local structure helps learning optimized automata in recurrent neural networks. Zurich Open Repository and Archive (University of Zurich). 1–7. 1 indexed citations

12.

Binas, Jonathan, Ueli Rutishauser, Giacomo Indiveri, & Michael Pfeiffer. (2014). Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity. Frontiers in Computational Neuroscience. 8. 68–68. 27 indexed citations

13.

Neftci, Emre, Jonathan Binas, Ueli Rutishauser, et al.. (2013). Synthesizing cognition in neuromorphic electronic systems. Proceedings of the National Academy of Sciences. 110(37). E3468–76. 101 indexed citations

14.

Fenwick, Oliver, Johannes K. Sprafke, Jonathan Binas, et al.. (2011). Linear and Cyclic Porphyrin Hexamers as Near-Infrared Emitters in Organic Light-Emitting Diodes. Nano Letters. 11(6). 2451–2456. 104 indexed citations

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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