• RoBERTa

  • Referenced in 24 articles [sw32571]
  • Robustly Optimized BERT Pretraining Approach. RoBERTa iterates on BERT’s pretraining procedure, including training...
  • MixTrain

  • Referenced in 1 article [sw31370]
  • attacks. The most promising defenses, adversarially robust training and verifiably robust training, have limitations that ... restrict their practical applications. The adversarially robust training only makes the networks robust against ... interval gradients. By contrast, verifiably robust training provides protection against any L-p norm-bounded ... computational and memory overhead than adversarially robust training. We propose two novel techniques, stochastic robust...
  • PaRoT

  • Referenced in 1 article [sw31366]
  • acceptance of these types of systems. Robust training --- training to minimize excessive sensitivity to small ... address this challenge. However, existing robust training tools are inconvenient to use or apply ... barrier to entry. Our framework enables robust training to be performed on arbitrary DNNs without ... real-world industrial application: training a robust traffic light detection network...
  • mixup

  • Referenced in 11 articles [sw35857]
  • favor simple linear behavior in-between training examples. Our experiments on the ImageNet-2012, CIFAR ... labels, increases the robustness to adversarial examples, and stabilizes the training of generative adversarial networks...
  • Scoredist

  • Referenced in 3 articles [sw35538]
  • Scoredist: A simple and robust protein sequence distance estimator. Results: We propose a correction-based ... methods using three evolutionary models for both training and testing Dayhoff, Jones-Taylor-Thornton ... optimal matrix methods, yet substantially more robust. When trained on one model but tested ... fast to implement and run, and combines robustness with accuracy. Scoredist has been incorporated into...
  • DeepTrack

  • Referenced in 2 articles [sw27576]
  • DeepTrack: learning discriminative feature representations online for robust visual tracking. Deep neural networks, albeit their ... training samples. In this work, we present an efficient and very robust tracking algorithm using ... Gradient Descent approach in CNN training with a robust sample selection mechanism. The sampling mechanism ... training. Equipped with this novel updating algorithm, the CNN model is robust to some long...
  • advertorch

  • Referenced in 1 article [sw32885]
  • various implementations for attacks, defenses and robust training methods. advertorch is built on PyTorch (Paszke...
  • GANSim

  • Referenced in 4 articles [sw40967]
  • inspection and quantitative assessment. The trained generators are quite robust in generating high-quality facies...
  • SketchREAD

  • Referenced in 5 articles [sw17612]
  • construct, and either are fragile or accomplish robustness by severely limiting the designer’s drawing ... that domain; no training data or programming is necessary. Robustness to the ambiguity and uncertainty...
  • GENETAG

  • Referenced in 5 articles [sw35526]
  • would have been more robust than word-based indices. GENETAG Train, Test and Round1 data...
  • FStitch

  • Referenced in 1 article [sw18729]
  • Markov model (HMM) and logistic regression to robustly classify which regions of the genome ... accurate, dependent on very little training data, robust to varying read depth, annotation agnostic...
  • RobBERT

  • Referenced in 2 articles [sw37743]
  • used RoBERTa, a robustly optimized BERT approach, to train a Dutch language model called RobBERT...
  • DeepTorrent

  • Referenced in 1 article [sw40013]
  • learning techniques are also employed to train the robustness predictor. Empirical benchmarking experiments demonstrate DeepTorrent...
  • MAPPOS

  • Referenced in 1 article [sw39535]
  • MAPPOS employs machine learning techniques to train a robust classifier from a small number...
  • SVMTool

  • Referenced in 5 articles [sw07975]
  • based tagger is robust and flexible for feature modelling (including lexicalization), trains efficiently with almost...
  • ApolloScape

  • Referenced in 6 articles [sw36630]
  • training and system evaluation is still a bottleneck for developing robust perception models. In this...
  • RBoost

  • Referenced in 3 articles [sw29975]
  • contribute to the robustness of the proposed algorithms to the noisy training and testing samples...
  • HCP

  • Referenced in 2 articles [sw28402]
  • required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant ... flexible and can be well pre-trained with a large-scale single-label image dataset...
  • AutoGluon-Tabular

  • Referenced in 2 articles [sw40229]
  • AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data. We introduce AutoGluon-Tabular, an open ... only a single line of Python to train highly accurate machine learning models ... many models offers better use of allocated training time than seeking out the best ... Benchmark reveal that AutoGluon is faster, more robust, and much more accurate. We find that...