MétaCan
ENFR
Menu
Cohort builder

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.

Export CSVExport JSONAPI query

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Neural Information Processing Systems
Topic
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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.

affaffiliation
fundfunder
venuejournal
aboutaboutness

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 ·
Results by year
20002021
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
208 works in the cohort · of 4,299,418page 3 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
Semiparametric Differential Graph Models
Pan Xu, Quanquan Gu
2016· article· en· Neural Information Processing Systems· Mathematics
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
Adaptive Gradient Quantization for Data-Parallel SGD
Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy, Ali Ramezani-Kebrya
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Wormholes Improve Contrastive Divergence
Max Welling, Andriy Mnih, Geoffrey E. Hinton
2003· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
13
citations
affno abstractunlabeled
Escaping the Gravitational Pull of Softmax
Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020· article· en· Neural Information Processing Systems· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Dualing GANs
Yujia Li, Alexander G. Schwing, Kuan-Chieh Wang, Richard S. Zemel
2017· article· en· Neural Information Processing Systems· Physics and Astronomy
machine prediction:candidate · noneconsensus · none
13
citations
affunlabeled
Gradient Estimation with Stochastic Softmax Tricks
Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Maximum Entropy Monte-Carlo Planning
Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
12
citations
affno abstractunlabeled
Differentiable Meta-Learning of Bandit Policies.
Craig Boutilier, Chih‐Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
2020· article· en· Neural Information Processing Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
The Forget-me-not Process
Kieran Milan, Joel Veness, James E. Kirkpatrick, Michael Bowling, Anna Koop, Demis Hassabis
2016· article· en· Neural Information Processing Systems· Decision Sciences
machine prediction:candidate · noneconsensus · none
12
citations
affunlabeled
Unsupervised Text Generation by Learning from Search
Jingjing Li, Zichao Li, Lili Mou, Xin Jiang, Michael R. Lyu, Irwin King
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
10
citations
affunlabeled
Universal Boosting Variational Inference
Trevor Campbell, Xinglong Li
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Adversarial Example Games
Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien +1 more
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
8
citations
affunlabeled
Multitask Spectral Learning of Weighted Automata
Guillaume Rabusseau, Borja Balle, Joëlle Pineau
2017· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
A PAC-Bayes approach to the Set Covering Machine
François Laviolette, Mario Marchand, Mohak Shah
2005· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Off-policy Learning with Options and Recognizers
Doina Precup, Cosmin Păduraru, Anna Koop, Richard S. Sutton, Satinder Singh
2005· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Value-driven Hindsight Modelling
Arthur Guez, Fabio Viola, Théophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup +2 more
2020· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
← previousnext →

How this was built: Screen · Findings · About