Machine Learning Research
AI is good at tracking objects in two dimensions. A new model processes video from a camera with a depth sensor to predict how objects move through space.
Machine Learning Research
Wouldn’t it be great to see around corners? Deep learning researchers are working on it. Researchers developed deep-inverse correlography, a technique that interprets reflected light to reveal objects outside the line of sight.
Machine Learning Research
AI’s ability to transfer a person’s face from a source photo onto someone in a target photo doesn’t work so well when the target face is partially obscured by, say, eyeglasses, a veil, or a hand. A new technique handles such occlusions.
Machine Learning Research
In an online dating profile, the photo that highlights your physical beauty may not be the one that makes you look smart or honest — also important traits in a significant other. A new neural network helps pick the most appealing shots.
Machine Learning Research
Female giant pandas are fertile for only 24 to 36 hours a year: Valentine’s Day on steroids. A new neural network alerts human keepers when a panda couple mates.
Machine Learning Research
A protein’s biological function depends largely on its three-dimensional shape, but deducing its shape from its sequence of amino acids has been a longstanding problem. Researchers at DeepMind reveal how they used deep learning to solve the puzzle.
Machine Learning Research
Neural audio synthesizers like WaveRNN or GANSynth produce impressive sounds, but they require large, data-hungry neural networks. A new code library beefs up the neural music studio with efficient sound modules based on traditional synthesizer designs.
Machine Learning Research
School teachers may not like to hear this, but sometimes you get the best answer by peeking at your neighbor’s paper. A new language model framework peeks at the training data for context when making a prediction.
Machine Learning Research
A new system marks a step forward in converting text to speech: It’s fast at inference, reduces word errors, and provides some control over the speed and inflection of generated speech.What’s new: Yi Ren, Yangjun Ruan, and their co-authors at Zhejiang
Machine Learning Research
End-to-end backpropagation and labeled data are the peanut butter and chocolate of deep learning. However, recent work suggests that neither is necessary to train effective neural networks to represent complex data.
Machine Learning Research
Softmax commonly computes probabilities in a classifier’s output layer. But softmax isn’t always accurate in complex tasks — say, in a natural-language task, when the length of word vectors is much smaller than the number of words in the vocabulary.
Machine Learning Research
In tasks that involve generating natural language, neural networks often map an input sequence of words to an output sequence of words. Facebook researchers used a similar technique on sequences of mathematical symbols, training a model to map math problems to math solutions.