Working with IBM Research, RPI has created a first-of-its-kind, six-week credit-bearing course in Mandarin taught in the school’s Cognitive and Immersive Systems Laboratory.
At CVPR 2019, IBM researchers introduce techniques to interpret visually descriptive language to generate compositional scene representations from textual descriptions.
At CVPR 2019, IBM researchers introduce an improved method to bridge the semantic gap between visual scenes and language to produce diverse, creative and human-like captions.
Data augmentation is one of the leading methods to tackle the problem of few-shot learning, but current synthesis approaches only address the scenario of a single label per image, when in reality real life images may contain multiple objects. The IBM team came up with a novel technique for synthesizing samples with multiple labels.
Deep neural networks have demonstrated good results for few-shot learning. However, very few works have investigated the problem of few-shot object detection. A team of IBM researchers developed a novel approach for Distance Metric Learning (DML).
New techniques make fine tuning an AI model more efficient when doing transfer learning
IBM researchers, in collaboration with NYU and MIT, propose a novel alternative to backprop at ICML 2019 that offers competitive performance.
Understanding of the macroscopic behavior of deep learning neural networks.
At the 2019 VLSI, IBM researchers will present three papers that provide novel solutions to AI computing based on analog devices.
Scientists in IBM Research-Brazil developed a method based on GANs and hand sketches to generate realistic synthetic seismic images.
At the 36th International Conference on Machine Learning (ICML 2019), June 10–15 in Long Beach, CA, IBM Research AI will present recent technical advances in machine learning for AI and data science. We’ve led the exploration and development of machine learning technologies for decades, and now we’re progressing the AI field through our portfolio of […]