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Found 23 papers, 8 papers with code
Predator Prey Scavenger Model using Holling's Functional Response of Type III and Physics-Informed Deep Neural Networks
After the neural network, the hence-found parameters are fine-tuned using the Broyden-Fletcher-Goldfarb-Shanno algorithm.
Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health
Large language models (LLMs) have shown promising capabilities in healthcare analysis but face several challenges like hallucinations, parroting, and bias manifestation.
Apple Intelligence Foundation Language Models
We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute.
PhilHumans: Benchmarking Machine Learning for Personal Health
The use of machine learning in Healthcare has the potential to improve patient outcomes as well as broaden the reach and affordability of Healthcare.
Ask the experts: sourcing high-quality datasets for nutritional counselling through Human-AI collaboration
We release HAI-coaching, the first expert-annotated nutrition counselling dataset containing ~2. 4K dietary struggles from crowd workers, and ~97K related supportive texts generated by ChatGPT.
VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings
Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emotion Classification from essays written in reaction to news articles.
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
In this work, we introduce Semantic Pyramid AutoEncoder (SPAE) for enabling frozen LLMs to perform both understanding and generation tasks involving non-linguistic modalities such as images or videos.
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations.
Optimization of rule-based energy management strategies for hybrid vehicles using dynamic programming
The popular vehicle dynamic model used in many energy management optimization studies does not capture the vehicle dynamics that the in-vehicle measurement system does.
Practice Makes a Solver Perfect: Data Augmentation for Math Word Problem Solvers
Extensive experiments on two benchmark datasets across three state-of-the-art MWP solvers show that proposed methods increase the generalization and robustness of existing solvers.
Anno-MI: A Dataset of Expert-Annotated Counselling Dialogues
Research on natural language processing for counselling dialogue analysis has seen substantial development in recent years, but access to this area remains extremely limited due to the lack of publicly available expert-annotated therapy conversations.
Pneumonia Detection in Chest X-Rays using Neural Networks
The RSNA benchmark MAP score is 0. 25, but using the Mask RCNN model on a stratified sample of 3017 along with image augmentation gave a MAP score of 0. 15.
Adversarial Examples for Evaluating Math Word Problem Solvers
Standard accuracy metrics have shown that Math Word Problem (MWP) solvers have achieved high performance on benchmark datasets.
Towards Detecting Need for Empathetic Response in Motivational Interviewing
Empathetic response from the therapist is key to the success of clinical psychotherapy, especially motivational interviewing.
TF-IDF vs Word Embeddings for Morbidity Identification in Clinical Notes: An Initial Study
Today, we are seeing an ever-increasing number of clinical notes that contain clinical results, images, and textual descriptions of patient's health state.
Action detection using a neural network elucidates the genetics of mouse grooming behavior
Automated detection of complex animal behaviors remains a challenging problem in neuroscience, particularly for behaviors that consist of disparate sequential motions.
An empirical study of Conv-TasNet
Furthermore, we offer insights into the generalization capabilities of Conv-TasNet and the potential value of improvements to the encoder/decoder.
Prediction of Malignant & Benign Breast Cancer: A Data Mining Approach in Healthcare Applications
As a potential contributor to state-of-art technology development, data mining finds a multi-fold application in predicting Brest cancer.
Image De-Noising For Salt and Pepper Noise by Introducing New Enhanced Filter
In this paper a new method for the enhancement of grayscale images is introduced, when images are corrupted by fixed valued impulse noise (salt and pepper noise).
A Conjoint Application of Data Mining Techniques for Analysis of Global Terrorist Attacks -- Prevention and Prediction for Combating Terrorism
Terrorism has become one of the most tedious problems to deal with and a prominent threat to mankind.
Comparative Performance Analysis of Image De-noising Techniques
Objective of this paper is to present brief account on types of noises, its types and different noise removal algorithms.
Voice Conversion with Conditional SampleRNN
Here we present a novel approach to conditioning the SampleRNN generative model for voice conversion (VC).
Edge Detection Based Shape Identification
Index Terms: Edge Detection, Area Calculation, Shape Detection, Object Recognition
