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Tag: Conditional
Penguins Acquire Conditional 2025 First-Round Pick and Three Players From Vancouver for Marcus Pettersson and Drew O’Connor
The Pittsburgh Penguins have acquired the New York Rangers’ 2025 first-round draft pick (conditional), forward Danton Heinen, defenseman Vincent Desharnais, as well as 2024 third-round draft pick Melvin Fernstrom from the Vancouver Canucks in exchange for defenseman Marcus Pettersson and forward Drew O’Connor, it was announced today by President of Hockey Operations and General Manager Kyle Dubas.
“Moving two long-time Penguins is never an easy decision,” said Dubas. “Marcus and Drew have competed day-in and day-out for the organization since the day they arrived. Both players are high-quality people, highly competitive players and zero maintenance for their fellow teammates and the staff of the Penguins.”
As part of the trade, Pittsburgh will receive whichever of the New York Rangers’ 2025 or 2026 first-round draft picks that Vancouver receives as part of their trade with the New York Rangers earlier today.
The acquisition of the conditional 2025 first-round pick gives the Penguins 29 selections over the next three NHL drafts, which includes four first-round selections and 15 picks in the first three rounds. No team has more draft picks, or selections in the first three rounds, over the next three NHL Drafts than Pittsburgh.
“Tonight’s trade continues to move us in the direction set one year ago which is to continue to add young prospects, young players, and draft capital to the Penguins as we chart our course to return the club back into contention as urgently as possible,” said Dubas. “We are pleased to add Danton Heinen back to the Penguins and Vincent Desharnais to the club and look forward to seeing both in uniform in the coming days. The addition of Melvin Fernstrom also gives us a prospect that was highly regarded at the 2024 NHL Draft, and the Rangers’ first-round draft pick provides us with another strong asset that we can use to acquire an elite young player in the draft or via trade.”
Heinen is signed through the 2025-26 campaign and his contract carries an average annual value of $2.25 million. Desharnais is signed through the 2025-26 season and his contract carries an average annual value of $2 million.
The 6-foot-2, 195-pound Heinen returns for his second stint with the Penguins, previously playing in Pittsburgh from 2021-23. Heinen has skated in parts of nine seasons in the NHL split between Boston, Anaheim, Pittsburgh and Vancouver and has tallied 93 goals, 136 assists and 229 points in 537 career games. This season, Heinen has registered six goals, 11 assists and 17 points in 50 games with Vancouver.
Heinen established a career high in goals (18) and power-play goals (3) as a member of the Penguins in 2021-22. His career-high assist and point totals were set with the Bruins in 2017-18, tallying 31 helpers and 47 points that season.
The Langley, British Columbia native has 48 games of Stanley Cup Playoff experience with Pittsburgh and Boston, where he’s picked up six goals, seven assists, 13 points and is plus-5.
Prior to his professional career, Heinen spent two seasons playing collegiate hockey at the University of Denver from 2014-16. In 81 career games, Heinen scored 36 goals, 57 assists and 93 points.
Heinen was originally drafted in the fourth round (116th overall) of the 2014 NHL Draft by Boston.
Desharnais is in his third NHL season and has tallied three assists in 34 games. The 6-foot-7, 226-pound defenseman has played in 148 career NHL games with Vancouver and Edmonton, tallying one goal, 18 assists and 19 points. He has also skated in 28 career playoff games, tallying three assists with the Oilers.
The Laval, Quebec native began his professional career skating in parts of four seasons in the American Hockey League between 2019-23 with Bakersfield. He recorded five goals, 34 assists and 39 points in 122 career AHL games.
Desharnais played four seasons of collegiate hockey with Providence College, tallying 29 points (8G-21A) in 131 games between 2015-19.
Desharnais was originally drafted in the seventh round (183rd overall) of the 2016 NHL Draft by Edmonton.
Fernstrom, 18, is currently playing overseas with Orebro HK of the SHL, Sweden’s top professional league. In 35 games with Orebro HK, the 6-foot-1, 185-pound forward has notched three goals, five assists and eight points. He’s also suited up for 12 games with Orebro HK J20 in Sweden’s top junior hockey league, registering 11 goals, seven assists and 18 points.
Prior to being drafted by Vancouver in the third round (93rd overall) of the 2024 NHL draft, the native of Balsta, Sweden represented his home country at the 2024 World Under-18 Championship, bringing home a bronze medal.
The Pittsburgh Penguins have made a major trade with the Vancouver Canucks, acquiring a conditional 2025 first-round pick and three players in exchange for Marcus Pettersson and Drew O’Connor.The Penguins are adding to their future draft capital with the acquisition of the conditional first-round pick, which could prove to be a valuable asset down the line. In addition, they are bringing in three players from Vancouver who will add depth and versatility to their roster.
On the other side of the trade, the Canucks are getting a solid defenseman in Pettersson and a promising young forward in O’Connor. This trade could benefit both teams as they look to strengthen their rosters for the remainder of the season and beyond.
It will be interesting to see how these new additions impact both teams as they continue their pursuit of success in the NHL. Stay tuned for more updates on this trade and its implications for both the Penguins and the Canucks.
Tags:
Penguins trade news, Vancouver Canucks trade update, NHL trade deadline, Pittsburgh Penguins trade analysis, Marcus Pettersson trade details, Drew O’Connor trade details, 2025 first-round draft pick acquisition, NHL trade rumors
#Penguins #Acquire #Conditional #FirstRound #Pick #Players #Vancouver #Marcus #Pettersson #Drew #OConnorAn Introduction to Conditional Random Fields (Foundations and Trends(r) in Machine Learning)
Price:$85.00– $77.49
(as of Jan 22,2025 06:51:39 UTC – Details)
Publisher : Now Publishers (August 23, 2012)
Language : English
Paperback : 120 pages
ISBN-10 : 160198572X
ISBN-13 : 978-1601985729
Item Weight : 6.2 ounces
Dimensions : 6.14 x 0.25 x 9.21 inches
Conditional Random Fields (CRFs) are a popular and powerful framework for modeling structured prediction tasks in machine learning. In this post, we will provide an introduction to CRFs, focusing on the foundational concepts and recent advances in the field.CRFs are a type of probabilistic graphical model that captures dependencies between input variables and output variables. Unlike traditional models such as hidden Markov models or naive Bayes classifiers, CRFs allow for complex and flexible modeling of structured data, such as sequences, graphs, or images.
One of the key advantages of CRFs is their ability to model correlations between neighboring variables in the output space. This makes them particularly well-suited for tasks such as natural language processing, speech recognition, and computer vision, where the output is inherently structured and sequential.
In recent years, there has been significant progress in developing efficient algorithms for training and inference in CRFs, making them a practical choice for a wide range of machine learning applications. Additionally, researchers have explored extensions and generalizations of CRFs, such as deep CRFs and hierarchical CRFs, to further improve their performance and applicability.
Overall, CRFs are a versatile and powerful tool for modeling structured prediction tasks, and understanding their foundations and recent developments can be valuable for both researchers and practitioners in the field of machine learning. If you are interested in learning more about CRFs, we recommend checking out the book “Conditional Random Fields (Foundations and Trends® in Machine Learning)” for a comprehensive overview of the topic.
#Introduction #Conditional #Random #Fields #Foundations #Trendsr #Machine #Learning,machine learning: an applied mathematics introduction
