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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

208 results · 1 filter active ·
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20002021
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
208 works in the cohort · of 4,299,418page 1 of 5

Labels cover 0 of 208 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 208 of 208 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
Probabilistic Matrix Factorization
Andriy Mnih, Ruslan Salakhutdinov
2007· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
3,578
citations
affunlabeled
Saliency Based on Information Maximization
Neil D. B. Bruce, John K. Tsotsos
2005· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
1,100
citations
affunlabeled
Replicated Softmax: an Undirected Topic Model
Geoffrey E. Hinton, Ruslan Salakhutdinov
2009· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
442
citations
affunlabeled
Deep Sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Russ R. Salakhutdinov, Alexander J. Smola
2017· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
318
citations
affunlabeled
Parametric Bandits: The Generalized Linear Case
Sarah Filippi, Olivier Cappé, Aurélien Garivier, Csaba Szepesvári
2010· article· en· Neural Information Processing Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
261
citations
affunlabeled
Supervised Learning with Tensor Networks
E. Miles Stoudenmire, David J. Schwab
2016· article· en· Neural Information Processing Systems· Mathematics
machine prediction:candidate · noneconsensus · none
214
citations
affunlabeled
Lookahead Optimizer: k steps forward, 1 step back
Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
176
citations
affunlabeled
Multi-Prediction Deep Boltzmann Machines
Ian Goodfellow, Mehdi Mirza, Aaron Courville, Yoshua Bengio
2013· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
116
citations
affunlabeled
Residual Flows for Invertible Generative Modeling
Ricky T. Q. Chen, Jens Behrmann, David Duvenaud, Joern-Henrik Jacobsen
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
109
citations
affunlabeled
A Better Way to Pretrain Deep Boltzmann Machines
Geoffrey E. Hinton, Ruslan Salakhutdinov
2012· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
106
citations
affunlabeled
Fast AutoAugment
Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, Sungwoong Kim
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
104
citations
affunlabeled
Learning Deep Parsimonious Representations
Renjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun
2016· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
90
citations
affunlabeled
The pigeon as particle filter
Nathaniel D. Daw, Aaron Courville
2007· article· en· Neural Information Processing Systems· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
81
citations
affunlabeled
Learning from Limited Demonstrations
Beomjoon Kim, Amir massoud Farahmand, Joëlle Pineau, Doina Precup
2013· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
72
citations
affunlabeled
Proximal Deep Structured Models
Shenlong Wang, Sanja Fidler, Raquel Urtasun
2016· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations
affunlabeled
Generating more realistic images using gated MRF's
Marc’Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton
2010· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
63
citations
affunlabeled
Satisfying real-world goals with dataset constraints
Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander
2016· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
55
citations
affunlabeled
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso, Luca Cavalleri, Dominique Beaini, Píetro Lió, Petar Veličković
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
51
citations
affunlabeled
Stop wasting my gradients: practical SVRG
Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konečný, Scott Sallinen
2015· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
50
citations
affno abstractunlabeled
Information Maximization for Few-Shot Learning
Malik Boudiaf, Imtiaz Masud Ziko, Jérôme Rony, José Dolz, Pablo Piantanida, Ismail Ben Ayed
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
49
citations
affunlabeled
The Gaussian Process Density Sampler
Iain Murray, David Mackay, Ryan P. Adams
2008· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
48
citations
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