default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGuillaume Lajoie
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c27]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR 2024- [c26]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. ICLR 2024 - [c25]Nanda H. Krishna
, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie:
Sufficient conditions for offline reactivation in recurrent neural networks. ICLR 2024 - [c24]Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan:
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. ICLR 2024 - [c23]Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie:
How connectivity structure shapes rich and lazy learning in neural circuits. ICLR 2024 - [c22]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR 2024 - [i40]Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie:
Does learning the right latent variables necessarily improve in-context learning? CoRR abs/2405.19162 (2024) - [i39]Ezekiel Williams, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Alexandre Payeur, Matthew G. Perich, Luca Mazzucato, Guillaume Lajoie:
Expressivity of Neural Networks with Random Weights and Learned Biases. CoRR abs/2407.00957 (2024) - [i38]Seijin Kobayashi, Simon Schug, Yassir Akram, Florian Redhardt, Johannes von Oswald, Razvan Pascanu, Guillaume Lajoie, João Sacramento:
When can transformers compositionally generalize in-context? CoRR abs/2407.12275 (2024) - [i37]Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien:
Accelerating Training with Neuron Interaction and Nowcasting Networks. CoRR abs/2409.04434 (2024) - [i36]Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy:
Latent Representation Learning for Multimodal Brain Activity Translation. CoRR abs/2409.18462 (2024) - 2023
- [j16]Erica L. Busch, Jessie Huang, Andrew Benz, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy, Nicholas B. Turk-Browne:
Multi-view manifold learning of human brain-state trajectories. Nat. Comput. Sci. 3(3): 240-253 (2023) - [j15]Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas:
LEAD: Min-Max Optimization from a Physical Perspective. Trans. Mach. Learn. Res. 2023 (2023) - [j14]Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake Aaron Richards:
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. Trans. Mach. Learn. Res. 2023 (2023) - [c21]MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky:
Reliability of CKA as a Similarity Measure in Deep Learning. ICLR 2023 - [c20]Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad P. Körding, Blake Aaron Richards:
How gradient estimator variance and bias impact learning in neural networks. ICLR 2023 - [c19]Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie:
Flexible Phase Dynamics for Bio-Plausible Contrastive Learning. ICML 2023: 37042-37065 - [c18]Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer:
A Unified, Scalable Framework for Neural Population Decoding. NeurIPS 2023 - [c17]Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake A. Richards, Guillaume Lajoie:
Formalizing locality for normative synaptic plasticity models. NeurIPS 2023 - [i35]Xu Ji, Eric Elmoznino, George Deane, Axel Constant, Guillaume Dumas, Guillaume Lajoie, Jonathan Simon, Yoshua Bengio:
Sources of Richness and Ineffability for Phenomenally Conscious States. CoRR abs/2302.06403 (2023) - [i34]Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan:
Steerable Equivariant Representation Learning. CoRR abs/2302.11349 (2023) - [i33]Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie:
Flexible Phase Dynamics for Bio-Plausible Contrastive Learning. CoRR abs/2302.12431 (2023) - [i32]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR abs/2305.19394 (2023) - [i31]Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie:
Discrete, compositional, and symbolic representations through attractor dynamics. CoRR abs/2310.01807 (2023) - [i30]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR abs/2310.02423 (2023) - [i29]Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan:
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. CoRR abs/2310.03734 (2023) - [i28]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. CoRR abs/2310.04363 (2023) - [i27]Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie:
How connectivity structure shapes rich and lazy learning in neural circuits. CoRR abs/2310.08513 (2023) - [i26]Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael J. Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer:
A Unified, Scalable Framework for Neural Population Decoding. CoRR abs/2310.16046 (2023) - 2022
- [j13]Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie:
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. Frontiers Appl. Math. Stat. 8 (2022) - [j12]Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mach. Intell. 4(6): 564-573 (2022) - [j11]Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mac. Intell. 4(11): 1053 (2022) - [j10]Maximilian Puelma Touzel, Paul Cisek, Guillaume Lajoie:
Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost. PLoS Comput. Biol. 18(5) (2022) - [j9]Thomas George, Guillaume Lajoie, Aristide Baratin:
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. Trans. Mach. Learn. Res. 2022 (2022) - [c16]Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP 2022: 5647-5651 - [c15]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. ICLR 2022 - [c14]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. ICLR 2022 - [c13]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. ICML 2022: 17669-17690 - [c12]Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA 2022: 171-184 - [c11]Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy:
Learning Shared Neural Manifolds from Multi-Subject FMRI Data. MLSP 2022: 1-6 - [c10]Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie:
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. NeurIPS 2022 - [c9]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? NeurIPS 2022 - [i25]Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy:
Learning shared neural manifolds from multi-subject FMRI data. CoRR abs/2201.00622 (2022) - [i24]Léo Gagnon, Guillaume Lajoie:
Clarifying MCMC-based training of modern EBMs : Contrastive Divergence versus Maximum Likelihood. CoRR abs/2202.12176 (2022) - [i23]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. CoRR abs/2203.01443 (2022) - [i22]Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie:
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR abs/2206.00823 (2022) - [i21]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? CoRR abs/2206.02713 (2022) - [i20]Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie:
On Neural Architecture Inductive Biases for Relational Tasks. CoRR abs/2206.05056 (2022) - [i19]Thomas George, Guillaume Lajoie, Aristide Baratin:
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. CoRR abs/2209.09658 (2022) - [i18]Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou:
From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR abs/2210.13774 (2022) - [i17]MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky:
Reliability of CKA as a Similarity Measure in Deep Learning. CoRR abs/2210.16156 (2022) - [i16]Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake A. Richards:
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. CoRR abs/2211.16607 (2022) - 2021
- [j8]Laura E. Suárez, Blake A. Richards, Guillaume Lajoie, Bratislav Misic:
Learning function from structure in neuromorphic networks. Nat. Mach. Intell. 3(9): 771-786 (2021) - [j7]Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish:
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33(8): 2087-2127 (2021) - [c8]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization via Neural Feature Alignment. AISTATS 2021: 2269-2277 - [c7]Olivier Tessier-Larivière, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie, Blake A. Richards:
PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks. NER 2021: 778-782 - [c6]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c5]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS 2021: 1256-1272 - [i15]Christian David Marton, Guillaume Lajoie, Kanaka Rajan:
Efficient and robust multi-task learning in the brain with modular task primitives. CoRR abs/2105.14108 (2021) - [i14]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR abs/2107.00848 (2021) - [i13]Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR abs/2107.12334 (2021) - [i12]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. CoRR abs/2110.09419 (2021) - [i11]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. CoRR abs/2112.03215 (2021) - 2020
- [c4]Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie:
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. Canadian AI 2020: 276-282 - [c3]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML 2020: 6972-6986 - [c2]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS 2020 - [i10]Stefan Horoi, Guillaume Lajoie, Guy Wolf:
Internal representation dynamics and geometry in recurrent neural networks. CoRR abs/2001.03255 (2020) - [i9]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR abs/2006.09471 (2020) - [i8]Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf, Guillaume Lajoie:
Advantages of biologically-inspired adaptive neural activation in RNNs during learning. CoRR abs/2006.12253 (2020) - [i7]Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie:
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. CoRR abs/2006.14123 (2020) - [i6]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR abs/2006.16981 (2020) - [i5]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization in Deep Learning: A View from Function Space. CoRR abs/2008.00938 (2020) - [i4]Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas:
LEAD: Least-Action Dynamics for Min-Max Optimization. CoRR abs/2010.13846 (2020) - [i3]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020)
2010 – 2019
- 2019
- [c1]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS 2019: 13591-13601 - [i2]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR abs/1905.12080 (2019) - [i1]Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Dimensionality compression and expansion in Deep Neural Networks. CoRR abs/1906.00443 (2019) - 2017
- [j6]Guillaume Lajoie, Nedialko I. Krouchev, John F. Kalaska, Adrienne L. Fairhall, Eberhard E. Fetz:
Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface. PLoS Comput. Biol. 13(2) (2017) - 2016
- [j5]Philippe Vincent-Lamarre, Guillaume Lajoie, Jean-Philippe Thivierge:
Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks. J. Comput. Neurosci. 41(3): 305-322 (2016) - [j4]Guillaume Lajoie, Lai-Sang Young:
Dynamic Signal Tracking in a Simple V1 Spiking Model. Neural Comput. 28(9): 1985-2010 (2016) - [j3]Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown:
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. PLoS Comput. Biol. 12(12) (2016) - 2014
- [j2]Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown:
Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. 8: 123 (2014) - 2011
- [j1]Guillaume Lajoie, Eric Shea-Brown:
Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps. SIAM J. Appl. Dyn. Syst. 10(4): 1232-1271 (2011)
Coauthor Index
Blake A. Richards
aka: Blake Aaron Richards
aka: Blake Aaron Richards
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-18 19:28 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
