jcohenadad
commented
1 year ago After digging a little, it looks like it uses JS code:
function milabib_onload(topics_list, paper_topics) {
--
| // Populate topics search
| let index = [];
| let topics = document.getElementById("milabib-topics-nav");
| for (let entry of topics_list.split(";")) {
| let [topic, n] = entry.split(":");
| let elem = document.createElement("span");
| elem.textContent = `${topic} (${n})`;
| elem.className = "topic2";
| elem.onclick = () => milabib_addToSearch(topic);
| topics.appendChild(elem);
| index.push(topic);
| }
|
| // Populate topics for each individual paper
| let paper_id = 0;
| for (let topics of paper_topics) {
| let topics_div = document.querySelector(`#P${paper_id} > .topics`);
| for (let topic_id of topics) {
| let elem = document.createElement("span");
| let topic = index[topic_id]
| elem.textContent = topic;
| elem.className = "topic";
| elem.onclick = () => milabib_addToSearch(topic);
| topics_div.appendChild(elem);
| }
| paper_id++;
| }
|
| // Apply search terms from the URL
| let search = decodeURIComponent(window.location.search);
| if (search.startsWith("?q=")) {
| search = search.substring(3);
| let sb = document.getElementById("milabib-search-input");
| sb.value = search;
| milabib_filter(search);
| }
| let sb = document.getElementById("milabib-search-input");
|
| if (true) {
| // Focus the searchbar
| sb.focus();
| }
| }
|
| milabib_kws = "computer science:2129;artificial intelligence:1043;machine learning:412;reinforcement learning:289;artificial neural network:270;deep learning:242;algorithm:228;task:197;theoretical computer science:190;pattern recognition:147;graph:146;generalization:145;mathematical optimization:133;inference:132;set:122;natural language processing:113;context:103;feature learning:102;psychology:101;representation:98;benchmark:94;robustness:90;medicine:85;mathematics:84;feature:78;recurrent neural network:75;process:75;leverage:73;neuroscience:72;convolutional neural network:69;applied mathematics:68;human computer interaction:68;code:67;biology:67;generative grammar:67;structure:66;domain:64;key:62;state:61;adversarial system:58;function:57;focus:55;computation:54;data science:54;segmentation:54;language model:53;image:51;space:50;embedding:50;entropy:50;probabilistic logic:49;computer vision:48;regularization:48;field:47;metric:46;sampling:44;robot:44;range:42;population:42;scalability:41;software:41;control:40;transformer:40;class:40;decoding methods:40;sequence:39;encoder:39;cluster analysis:39;sample:38;differentiable function:37;simple:37;convergence:37;mnist database:37;data mining:37;autoencoder:36;distributed computing:36;natural language:36;scale:36;quality:35;contrast:34;invariant:34;latent variable:34;estimator:34;variety:34;markov decision process:33;contextual image classification:33;ranking:33;transfer of learning:33;noise:33;interpretability:33;perspective:33;supervised learning:33;mutual information:32;information retrieval:32;visualization:32;cognition:31;bayesian probability:31;bellman equation:30;computational biology:30;classifier:30;gradient descent:29;empirical research:29;recommender system:29;speech recognition:29;variance:28;value:28;solver:28;work:28;cognitive psychology:28;matching:27;similarity:27;upper and lower bounds:27;neuroimaging:27;cognitive science:27;graph neural networks:27;training set:27;optimization problem:27;object:26;pipeline:26;generative model:26;forgetting:26;task analysis:26;path:25;baseline:25;encoding:25;real time computing:25;coronavirus disease 2019:25;software engineering:25;adaptation:25;discrete mathematics:25;computer engineering:25;sentence:25;state space:25;physics:25;distribution:24;question answering:24;training:24;heuristic:24;automatic summarization:24;inductive bias:23;parsing:23;node:23;heuristics:23;trajectory:23;kernel:23;signal:23;measure:23;deep neural networks:22;maximization:22;computer security:22;speedup:22;pruning:21;initialization:21;mechanism:21;syntax:21;feature extraction:21;reduction:21;semantics:21;overfitting:21;nonlinear system:21;manifold:21;cloud computing:21;selection:20;identification:20;stochastic gradient descent:20;medline:20;exploit:20;unsupervised learning:20;architecture:19;rate of convergence:19;internal medicine:19;variable:19;order:19;public health:19;active learning:19;tensor:18;dimension:18;integer programming:18;autism:18;interpolation:18;parametric statistics:18;consistency:18;materials science:18;bayesian inference:18;sensory system:18;linguistics:18;knowledge graph:18;term:17;channel:17;operations research:17;backpropagation:17;parallel computing:17;domain adaptation:17;component:17;gene:17;perception:17;disease:17;hyperparameter:17;meta learning:17;operator:16;modular design:16;world wide web:16;action:16;quadratic equation:16;computational complexity theory:16;discriminator:16;topology:16;source code:16;interface:16;robotics:16;probability distribution:16;spinal cord:16;translation:16;health care:16;stochastic process:16;stability:15;bottleneck:15;gaussian:15;flow:15;anomaly detection:15;dependency:15;image segmentation:15;pandemic:15;hierarchy:15;reliability:15;generator:15;discriminative model:15;constraint:15;variation:15;rendering:15;pixel:15;business:15;scheme:15;natural language understanding:15;continual learning:15;residual:15;rank:14;pure mathematics:14;econometrics:14;markov chain:14;construct:14;estimation:14;autoregressive model:14;constant:14;sociology:14;property:14;mobile device:14;network architecture:14;layer:14;chemistry:14;data collection:14;autism spectrum disorder:14;usability:14;biological neural network:14;radiology:14;political science:14;linear programming:14;data modeling:14;social media:14;norm:13;combinatorics:13;abstraction:13;edge:13;natural:13;series:13;bounded function:13;data structure:13;default mode network:13;importance sampling:13;flexibility:13;cohort:13;computer network:13;relevance:13;severe acute respiratory syndrome coronavirus 2:13;medical imaging:13;energy consumption:13;regret:13;python:13;protocol:13;function approximation:13;word:13;transformation:13;internet privacy:13;event:13;margin:12;information bottleneck method:12;conditional probability distribution:12;hessian matrix:12;convex function:12;temporal difference learning:12;overhead:12;integer:12;text mining:12;parameterized complexity:12;benchmarking:12;throughput:12;block:12;redundancy:12;ground truth:12;filter:12;rna:12;human brain:12;scattering:12;genome:12;markov process:12;point:12;relation:12;curse of dimensionality:12;feature vector:12;end to end principle:11;frame:11;eigenvalues and eigenvectors:11;lipschitz continuity:11;social relation:11;psychological intervention:11;regression:11;modality:11;resource:11;synchronization:11;dimensionality reduction:11;normalization:11;convolution:11;intersection:11;face:11;developmental psychology:11;test:11;imitation learning:11;regular polygon:11;quantization:11;matrix:11;transfer:10;modularity:10;prior probability:10;momentum:10;specialization:10;dynamics:10;sample size determination:10;treebank:10;nash equilibrium:10;lesion:10;asynchronous communication:10;software deployment:10;machine translation:10;coherence:10;multiple sclerosis:10;dynamic programming:10;taxonomy:10;aggregate:10;smoothness:10;biobank:10;correlation:10;stochastic computing:10;outcome:10;object detection:10;polar code:10;efficient energy use:10;minification:10;2019 20 coronavirus outbreak:10;algebra:10;computer hardware:10;boosting:10;clinical psychology:10;magnetic resonance imaging:10;diffusion mri:10;markov chain monte carlo:10;monte carlo method:10;multimedia:10;software development:10;maxima and minima:10;encode:10;trace:9;causal inference:9;stationary point:9;activation function:9;social isolation:9;loneliness:9;hippocampus:9;statistics:9;categorical variable:9;energy:9;finite state machine:9;line:9;topic model:9;the internet:9;convex optimization:9;expression:9;controller:9;transmission:9;signal processing:9;scaling:9;motion:9;acceleration:9;climate change:9;curriculum:9;data set:9;latency:9;domain knowledge:9;control theory:9;condensed matter physics:9;reproducibility:9;reinforcement:9;software system:9;learning environment:9;thompson sampling:9;linear function:9;combinatorial optimization:9;neocortex:9;dynamical systems theory:9;resolution:9;causality:9;equivariant map:9;lifelong learning:9;variance reduction:9;scheduling:9;shot:9;style:9;sigmoid function:9;equivalence:9;compiler:9;oracle:8;causal model:8;cognitive neuroscience of visual object recognition:8;geography:8;stochastic optimization:8;outlier:8;social neuroscience:8;meaning:8;joint probability distribution:8;drug discovery:8;popularity:8;embodied cognition:8;wavelet:8;logarithm:8;calibration:8;multi task learning:8;automaton:8;dna sequencing:8;personalization:8;time horizon:8;public relations:8;citizen science:8;mobile computing:8;medical physics:8;observable:8;affine transformation:8;precision medicine:8;emergency medicine:8;image translation:8;statistical physics:8;observability:8;knowledge transfer:8;structured prediction:8;extension:8;image processing:8;prefrontal cortex:8;density estimation:8;polar:8;resource allocation:8;decomposition:8;quadratic programming:8;partially observable markov decision process:8;mixture model:8;optimal control:8;winograd schema challenge:8;hyperparameter optimization:8;link:7;joint:7;power:7;counterfactual thinking:7;intelligent agent:7;affordance:7;bayes theorem:7;continuous optimization:7;random forest:7;tree:7;incentive:7;correctness:7;grid:7;sentiment analysis:7;iterative reconstruction:7;applied psychology:7;demography:7;routing:7;global positioning system:7;binary number:7;observational study:7;diffusion:7;message passing:7;spurious relationship:7;suite:7;transparency:7;successor cardinal:7;intensive care medicine:7;oncology:7;association:7;minimax:7;social cognition:7;voxel:7;relaxation:7;connectome:7;service:7;programming language:7;traceability:7;discrete choice:7;software quality:7;posterior probability:7;random walk:7;salience:7;resting state fmri:7;natural language generation:7;biological system:7;softmax function:7;interneuron:7;java:7;knowledge management:7;data point:7;duality:7;fixed point:7;rule based machine translation:7;linear model:7;bandwidth:7;support vector machine:7;modalities:7;matrix decomposition:7;constrained optimization:7;semi supervised learning:7;distillation:7;random variable:7;annotation:7;bisimulation:7;base:7;hidden markov model:7;information theory:7;credit assignment:7;database:7;gesture recognition:7;graphical model:7;risk analysis:7;democracy:7;electronic engineering:6;discretization:6;visual reasoning:6;current:6;branch and bound:6;adjacency matrix:6;cohort study:6;f1 score:6;magnetoencephalography:6;schizophrenia:6;in patient:6;stroke:6;diversity:6;malware:6;word order:6;attribution:6;writing style:6;authorship attribution:6;test set:6;complement:6;noise reduction:6;cache:6;source separation:6;dropout:6;ranging:6;masking:6;divergence:6;intervention:6;gradient method:6;molecular graph:6;black box:6;genome wide association study:6;genetic association:6;receiver operating characteristic:6;cover:6;adversary:6;vertex:6;transcriptome:6;time series:6;error detection and correction:6;engineering ethics:6;fidelity:6;discounting:6;pose:6;computational model:6;type:6;coupling:6;product:6;ode:6;causal structure:6;directed acyclic graph:6;open source:6;cyber physical system:6;5g:6;point cloud:6;time complexity:6;global illumination:6;resampling:6;infomax:6;factorization:6;pooling:6;big data:6;pairwise comparison:6;medical diagnosis:6;salient:6;particle filter:6;commonsense reasoning:6;electrophysiology:6;labeled data:6;euclidean geometry:6;gesture:6;constraint programming:6;column generation:6;vocabulary:6;utterance:6;consumption:6;parametrization:6;calcium imaging:6;smoothing:6;feed forward:6;local optimum:6;contact tracing:6;tracing:6;code generation:6;documentation:6;gene expression:6;electroencephalography:6;radiomics:6;phenotype:6;revenue:6;social network:6;user experience design:6;laplacian matrix:6;ontology:6;smart grid:6;language acquisition:6;euclidean distance:6;ray tracing:6;optogenetics:6;mechanical 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process:4;mathematical proof:4;social distance:4;environmental science:4;linear system:4;minor:4;symmetric matrix:4;information extraction:4;track:4;path tracing:4;categorization:4;isolation:4;excitatory postsynaptic potential:4;word embedding:4;models of neural computation:4;myelopathy:4;image quality:4;network structure:4;content:4;canonical correlation:4;cluster:4;scratch:4;emergency department:4;adverse effect:4;analytics:4;exponential family:4;cell biology:4;replication:4;minimum bounding box:4;genetics:4;langevin dynamics:4;conditional random field:4;personalized medicine:4;human robot interaction:4;calculus:4;job shop scheduling:4;bias of an estimator:4;confounding:4;semantic similarity:4;mobile robot:4;invertible matrix:4;training methods:4;video game:4;facial recognition system:4;dialog box:4;upsampling:4;polarization:4;exploratory research:4;motion planning:4;univariate:4;ensemble learning:4;genetic heterogeneity:4;learning rule:4;information access:4;public 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capture:4;media studies:4;radiance:4;lift:4;neural coding:4;mahalanobis distance:4;neuron:4;narrative:4;mathematical analysis:4;resilience:4;reachability:4;steady state:4;parvalbumin:4;search algorithm:4;recursion:4;inertial measurement unit:4;information sensitivity:4;blockchain:4;kronecker delta:4;network model:3;gumbel distribution:3;graph based:3;data efficiency:3;high probability:3;3d reconstruction:3;haptic technology:3;least squares:3;visual cortex:3;laplace operator:3;piecewise linear function:3;geolocation:3;collision:3;anomaly:3;social deprivation:3;etiology:3;proportional hazards model:3;parametric model:3;decision tree:3;normal distribution:3;theory of mind:3;monotone polygon:3;knapsack problem:3;biomarker:3;reputation:3;dashboard:3;voting:3;graph theory:3;attractor:3;cutting plane method:3;cardiology:3;astrocyte:3;bag of words model:3;data compression:3;applications of artificial intelligence:3;data access:3;coreference:3;cube:3;presentation:3;library science:3;random 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| milabib_onload(milabib_kws, milabib_paper_topics);</script> </div></div></div><div
| class=goToTop><imgI am wondering if there are RTD plugin that can do that... or if we can develop our own CSS classes.
Example: https://mila.quebec/en/publications/
It would be nice to reuse the same code as in the Mila website. Not sure if that's 'easily' possible via RTD