techtimes

Cognition SWE-1.7: RL on Top of RL Yields Near-Frontier Code at Low Cost

Cognition launched SWE-1.7 on Wednesday, the most capable model it has trained, and with it made a specific claim about reinforcement learning that the broader AI research community will be evaluating ...
IEEE

Distributional Policy Gradient With Distributional Value Function

Abstract: In this article, we propose a distributional policy-gradient method based on distributional reinforcement learning (RL) and policy gradient. Conventional RL algorithms typically estimate the ...
IEEE

Bayesian Local Sampling-Based Planning

Abstract: Sampling-based planning is the predominant paradigm for motion planning in robotics. Most sampling-based planners use a global random sampling scheme to guarantee probabilistic completeness.
BMJ

Our Health Counts Toronto: using respondent-driven sampling to unmask census undercounts of an urban indigenous population in Toronto, Canada

Objectives To provide evidence of the magnitude of census undercounts of ‘hard-to-reach’ subpopulations and to improve estimation of the size of the urban indigenous population in Toronto, Canada, ...
CBS

Improving the sampling strategy for the Community Innovation Survey using machine learning algorithms

National statistical institutes (NSI's) are increasingly interested in using non-probability data to produce official statistics. Examples are information on the internet, social media messages, ...
Investopedia

Sampling Distribution: Definition, How It's Used, and Example

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Thomas J. Brock is a CFA and CPA with more ...
VentureBeat

Researchers find adding this one simple sentence to prompts makes AI models way more creative

One of the coolest things about generative AI models — both large language models (LLMs) and diffusion-based image generators — is that they are "non-deterministic." That is, despite their reputation ...
GitHub

Flow Annealed Importance Sampling Bootstrap (FAB)

Code for the paper Flow Annealed Importance Sampling Bootstrap (FAB). FAB in JAX: See the JAX implementation of the FAB algorithm in the fab-jax repo. The fab-jax code is cleaner, faster and easier to ...
The Conversation

How a subfield of physics led to breakthroughs in AI – and from there to this year’s Nobel Prize

John J. Hopfield and Geoffrey E. Hinton received the Nobel Prize in physics on Oct. 8, 2024, for their research on machine learning algorithms and neural networks that help computers learn. Their work ...
C&EN

Configurational Sampling of All-Atom Solvated Membranes Using Hybrid Nonequilibrium Molecular Dynamics Monte Carlo Simulations

Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana−Champaign, Université de Lorraine, LPCT, F-54000 Nancy, France Article Views are the ...
Frontiers

Examining dependencies among different time scales in episodic memory – an experience sampling study

We re-examined whether different time scales such as week, day of week, and hour of day are independently used during memory retrieval as has been previously argued (i.e., independence of scales). To ...