However, it is expensive to retrain models from scratch. To address this problem, we propose the DeltaGrad algorithm for rapid retraining machine learning models based on information cached during the training phase. We provide both theoretical and empirical support for the effectiveness of DeltaGrad,...
Retraining a new model for application in different types of spectra, e.g., FTIR, for a different type of material can be time-consuming, labor-intensive, and often impractical due to the challenges of gathering and curating extensive data. This limitation poses a substantial obstacle to the ...
Standard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intra-ob
Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously ...
This can be achieved by a continuous retraining of the neural network with an extended image dataset that includes samples from multiple laboratories to account for variability in sample processing, as well as samples from different species and neural pathologies. With increasing numbers of annotated ...
To mitigate this issue, certain studies have focused on the development of parameterizable PINN models that can be used for model parameter estimation without the need for retraining. For instance, Sun et al. trained a PINN model to parametrically solve the Navier–Stokes equations to simulate ...
Retraining of study staff will be done to correct for any inconsistencies noted during monitoring and follow-up will be subsequently done by the study coordinator to ensure compliance. Given that the digital triage tool is community and health system level intervention, a data monitoring committee ...
The models, code, and datasets are provided for reproduction and extension of our results. Keywords: Energy expenditure, Estimation, Machine learning, Gait, Ground reaction forces, Electromyography Background The U.S. has an estimated 20 million people with ambu- latory disabilities due to age, ...
This can be achieved by a continuous retraining of the neural network with an extended image dataset that includes samples from multiple laboratories to account for variability in sample processing, as well as samples from different species and neural pathologies. With increasing numbers of annotated ...
models such as light-field microscopy39and multifocus microscopy40enables inferring volumetric neuronal activities at high speed. On the other hand, utilizing generative adversarial networks for enhancing the virtual data generation holds potential to further improve the performance of DeepWonder41. We ...